This disclosure is related to hierarchical data arrangements and, more particularly, to manipulating such data arrangements.
In a variety of fields, data or a set of data, may be represented in a hierarchical fashion. This form of representation may, for example, convey information, such as particular relationships between particular pieces of data and the like. However, manipulating such data representations is not straight-forward, particularly where the data is arranged in a complex hierarchy. Without loss of generality, one example may include a relational database. Techniques for performing operations on such a database, for example, are computationally complex or otherwise cumbersome. A continuing need, therefore, exists for additional techniques for manipulating data hierarchies.
Subject matter is particularly pointed out and distinctly claimed in the concluding portion of the specification. The claimed subject matter, however, both as to organization and method of operation, together with objects, features, and advantages thereof, may best be understood by reference of the following detailed description when read with the accompanying drawings in which:
In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the claimed subject matter. However, it will be understood by those skilled in the art that the claimed subject matter may be practiced without these specific details. In other instances, well-known methods, procedures, components and/or circuits have not been described in detail so as not to obscure the claimed subject matter.
Some portions of the detailed description which follow are presented in terms of algorithms and/or symbolic representations of operations on data bits or binary digital signals stored within a computing system memory, such as a computer memory. These algorithmic descriptions and/or representations are the techniques used by those of ordinary skill in the data processing arts to convey the substance of their work to others skilled in the art. An algorithm is here, and generally, considered to be a self-consistent sequence of operations and/or similar processing leading to a desired result. The operations and/or processing involve physical manipulations of physical quantities. Typically, although not necessarily, these quantities may take the form of electrical and/or magnetic signals capable of being stored, transferred, combined, compared and/or otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, data, values, elements, symbols, characters, terms, numbers, numerals and/or the like. It should be understood, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels. Unless specifically stated otherwise, as apparent from the following discussion, it is appreciated that throughout this specification discussions utilizing terms such as “processing”, “computing”, “calculating”, “determining” and/or the like refer to the actions and/or processes of a computing platform, such as a computer or a similar electronic computing device, that manipulates and/or transforms data represented as physical electronic and/or magnetic quantities within the computing platform's memories, registers, and/or other information storage, transmission, and/or display devices.
In a variety of fields, data or sets of data may be represented in a hierarchical fashion. This form of representation may, for example, convey information, such as particular relationships between particular pieces of data and the like. However, manipulating such data representations is not straight forward, particularly where the data is arranged in a complex hierarchy. Without loss of generality, one example may include a relational data base. Techniques for performing operations on such a data base for example, may be computationally complex or otherwise cumbersome. A continuing need, therefore, exists for additional techniques for manipulating data hierarchies.
As previously discussed, in a variety of fields, it is convenient or desirable to represent data, a set of data and/or other information in a hierarchical fashion. In this context, such a hierarchy of data shall be referred to as a “tree.” In a particular embodiment, a tree may comprise a finite, rooted, connected, unordered, acyclic graph. This is illustrated here, for example, in
As previously suggested, in a variety of contexts, it may be convenient and/or desirable to represent a hierarchy of data and/or other information using a structure, such as the embodiment illustrated in
One example of a BELT is illustrated by embodiment 200 of
Binary edge labeled trees may also be enumerated. Thus, for this particular embodiment, although the claimed subject matter is not limited in scope in this respect, a method of enumerating a set of trees begins with enumeration of an empty binary edge labeled tree and a one node binary edge labeled tree. Here, the empty tree is associated with the zero and has a symbolic representation as illustrated in
However, for this particular embodiment, although the claimed subject matter is not limited in scope in this respect, a method of enumerating a set of ordered trees may begin with enumeration of an empty binary edge labeled tree and a one node binary edge labeled tree. Thus, the empty tree is associated with the zero and has a symbolic representation as illustrated in
As illustrated, for this particular embodiment, and as previously described, the empty tree has zero nodes and is associated with the numeral zero. Likewise, the one node tree root comprises a single node and is associated with the numeral one. Thus, to obtain the tree at position two, a root node is attached and connected to the prior root node by an edge. Likewise, here, by convention, the edge is labeled with a binary zero. If, however, the tree formed by the immediately proceeding approach were present in the prior enumeration of trees, then a similar process embodiment is followed, but, instead, the new edge is labeled with a binary one rather than a binary zero. Thus, for example, in order to obtain the binary edge labeled tree for position three, a new root node is connected to the root node by an edge and that edge is labeled with a binary one.
Continuing with this example, to obtain the binary edge labeled tree for position four, observe that numeral four is the product of numeral two times numeral two. Thus, a union is formed at the root of two trees, where, here, each of those trees is associated with the positive natural numeral two. Likewise, to obtain the binary edge labeled tree for position five, begin with the binary edge labeled tree for position two and follow the previously articulated approach of adding a root and an edge and labeling it with a binary zero.
In this context, adding a root node and an edge and labeling it binary zero is referred to as a “zero-push” operation and adding a root node and an edge and labeling it binary one is referred to as a “one-push” operation. Based at least in part on the prior description, for this particular embodiment, it may now be demonstrated that if k is any positive natural numeral and a tree x is positioned at location k, then a non-composite numeral is associated with the zero-push of that tree and a non-composite numeral is associated with the one-push for that tree. Furthermore, the non-composite index of the zero-push of the tree comprises 2k−1, whereas the non-composite index of the one-push of the tree comprises 2k, where the index corresponds to the argument of the well-known Kleene enumeration on positive natural numerals of non-composite numerals, as illustrated, for example, in part in
In this context, the approach just described may be referred to as vectorizing non-composite numerals. In the embodiment just described, this was accomplished in pairs, although, of course, the claimed subject matter is not limited in scope in this respect. This may be accomplished in any number of numeral combinations, such as triplets, quadruplets, etc. Thus, using a quadruplet example, it is possible to construct trees such that if k is any positive natural numeral and a tree x is positioned at location k, then a non-composite numeral is associated with the zero-push of that tree, a non-composite numeral is associated with the one-push for that tree, a non-composite numeral is associated with the two-push for that tree, and a non-composite number is associated with the three-push for that tree. Furthermore, the index of the non-composite numeral is such that for a zero-push of the tree, the index comprises (4k−3), for a one-push of a tree, the index comprises (4k−2), for a two-push of a tree, the index comprises (4k−1), and for a three-push of a tree the index comprise (4k), where the index corresponds to the kleene enumeration of non-composite numerals, P(index), such as provided in
In the previously described enumeration of binary edged labeled trees, a mechanism may be employed to reduce or convert complex manipulations of hierarchical data to multiplication of natural numerals. For example, if it is desired to combine, or merge at their roots, two trees of hierarchical data, a complex task both computationally and graphically, instead, for this particular embodiment, the two trees may be converted to numerical data by using the previously described association embodiment between binary edge labeled trees and natural numerals. The resulting numerical data from the prior conversion may then be multiplied, and the resulting product may then be converted to a binary edge labeled tree by using a table look up of the previously described association embodiment. It is noted that a subtle distinction may be made between an enumeration embodiment and an association embodiment. Enumeration may comprise listing, in this example, a particular ordered embodiment of BELTs, whereas an association provides a relationship between, in this example, a particular ordered embodiment of BELTs and natural numerals. It is, of course, appreciated that many different enumeration and association embodiments may be employed to execute the operations discussed above Sand hereinafter, and the claimed subject matter is intended to cover all such enumeration and association embodiments.
Likewise, a process embodiment that is a reversal to the previously described embodiments may also be employed. Thus, complex hierarchies of data may be split or divided, when this is desired. For example, a binary edge labeled tree to be divided may be converted to a piece of numerical data, such as by using the previously described association embodiment. This data may then be factored into two pieces of numerical data whose product produces the previously mentioned piece of numerical data. These two pieces of numerical data may then be converted to trees, again, by using the prior association embodiment, for example.
Another form of manipulating hierarchical sets of data may involve ordering or hashing. This may be desirable for any one of a number of different operations to be performed on the sets of data. One approach is similar to the previously described embodiment. For example, it may be desired to order a given set of trees. Doing so may involve converting the trees to numerical data, as previously described, using an association embodiment. The numerical data may then be ordered and the numerical data may then be converted back to binary edge labeled trees using the previously described association embodiment, or an alternate association embodiment, for example.
It is noted that there may be any one of a number of different ways of converting from numerals or numerical data values to a binary edge labeled tree or from a binary string to a binary edge labeled tree, and vice-versa. Nonetheless, a convenient method for doing so with this particular embodiment includes storing a table providing an association embodiment between natural numerals, binary strings and binary edge labeled trees, such as the embodiment previously described. Thus, once it is desired to convert from one to the other, such as from a binary string to a BELT, from a natural numeral to a BELT, or vice-versa, for example, a table look up operation may be performed using the association embodiment.
Techniques for performing table look ups are well-known and well-understood. Thus, this will not be discussed in detail here. However, it shall be appreciated that any and all of the previously described and/or later described processing, operations, conversions, transformations, manipulations, etc. of strings, trees, numerals, data, etc. may be performed on one or more computing platforms or similar computing devices, such as those that may include a memory to store a table as just described, although, the claimed subject matter is not necessarily limited in scope to this particular approach. Thus, for example, a hierarchy of data may be formed by combining two or more hierarchies of data, such as by applying a previously described embodiment. Likewise, multiple hierarchies of data may be formed by splitting or dividing a particular hierarchy of data, again, such as by applying a previously described embodiment. Likewise, additional operations and/or manipulations of data hierarchies may be performed, such as ordering hierarchies of data and more. It is intended that the claimed subject matter cover such embodiments.
Much of the prior discussion was provided in the context of binary edge labeled trees. Nonetheless, as alluded to previously, binary edge labeled trees and binary node labeled trees may be employed nearly interchangeably to represent substantially the same hierarchy of data. In particular, a binary node labeled tree may be associated with a binary edge labeled tree where the nodes of the binary node labeled tree take the same values as the edges of the binary edge labeled tree, except that the root node of the binary node labeled tree may comprise a node having a zero value or a null value. Thus, rather than employing binary edge labeled trees, the previously described embodiments may alternatively be performed using binary node labeled trees. As one example embodiment, operations and/or manipulations may be employed using binary edge labeled trees and then the resulting binary edge labeled tree may be converted to a binary node labeled tree. However, in another embodiment, operations and/or manipulations may be performed directly using binary node labeled trees where a different association embodiment, that is, in this example, one that employs binary node labeled trees, is employed.
In accordance with the claimed subject matter, therefore, any tree, regardless of whether it is binary edge labeled, binary node labeled, non-binary, a feature tree, or otherwise, may be manipulated and/or operated upon in a manner similar to the approach of the previously described embodiments. Typically, different association embodiments shall be employed, depending at least in part, for example, upon the particular type of tree. For example, and as shall be described in more detail below in connection with
As previously noted, the claimed subject matter is not limited in scope to this particular example, however, as illustrated in more detail hereinafter, the tree illustrated in
In another embodiment, however, a particular tree may include null types or, more particularly, some node values denoted by the empty set. This is illustrated, for example, by the tree in
Likewise, in an alternative embodiment, a node labeled tree may comprise fixed length tuples of numerals. For such an embodiment, such multiple numerals may be combined into a single numeral, such as by employing Cantor pairing operations, for example. See, for example, Logical Number Theory, An Introduction, by Craig Smorynski, pp, 14-23, available from Springer-Verlag, 1991. This approach should produce a tree to which the previously described embodiments may then be applied. Furthermore, for one embodiment, a tree in which nodes are labeled with numerals or numerical data, rather than binary data, may be converted to a binary edge labeled tree and/or binary node labeled tree, and, for another embodiment, a tree in which edges are labeled with numerals or numerical data, rather than binary data, may be converted to a binary edge labeled tree and/or binary node labeled tree.
Furthermore, a tree in which both the nodes and the edges are labeled may be referred to in this context as a feature tree and may be converted to a binary edge labeled tree and/or binary node labeled tree. For example, without intending to limit the scope of the claimed subject matter, in one approach, a feature tree may be converted by converting any labeled node with its labeled outgoing edge to an ordered pair of labels for the particular node. Using the embodiment described above, this tree may then be converted to a binary edge labeled tree.
In yet another embodiment, for trees in which data labels do not comprise simply natural numerals, such as, as one example, trees that include negative numerals, such data labels may be converted to an ordered pair of numerals. For example, the first numeral may represent a data type. Examples include a data type such as negative, dollars, etc. As described above, such trees may also be converted to binary edge labeled trees, such as by applying the previously described embodiment, for example.
As previously described, trees may be employed to graphically represent a hierarchy of data or a hierarchy of a set of data. This has been illustrated in some detail for binary edge labeled trees, for example. As the previous figures, illustrate, however, such graphical hierarchical representations typically employ two spatial dimensions to depict the relationship among different pieces of data. This may be disadvantageous in some situations where a one dimensional representation or arrangement of symbols, such as is employed with alphabetic letters, for example, that are combined to create a linear collection of successive symbols or notations, such as words, would be more convenient.
According to an embodiment, a tree may be expressed as one or more “subtrees” merged at the root node of the tree. A subtree is coupled to the root node of the tree at an edge and independently has properties of a tree, except that the subtree is part of a larger tree. For example, here, a subtree comprises at least a “root” node coupled by an edge to a root node of the larger tree. Additional nodes and edges may be coupled to the root node of the subtree. While a subtree may comprise an edge coupled to the root node of the tree, the size and shape of the subtree may express information like that of a tree having the same size and shape as the subtree. The subtrees merged together at the root node of a tree may be referred to as “subtree children” of the tree node and any particular one of such subtrees may be referred to as a “subtree child” of the tree in this embodiment. Also, like a tree, a subtree may be represented as a natural numeral according to an association of trees with natural numerals as illustrated with reference to
According to an embodiment, a tree having a root node may be comprise one or more “rooted partial subtrees” (RPSTs) representing at least a portion of the hierarchical data represented by the tree. In this particular embodiment, a component RPST of a tree may comprise the same root node as the full tree, one or more other nodes in the tree coupled to the root node by intermediate nodes, the intermediate nodes themselves, and edges in the tree coupling the root node, the one or more other nodes and the intermediate nodes to one another. A component RPST of a full tree defines a connected path between the root node of the full tree and any other node in the component RPST along one or more edges in the tree, and any intermediate nodes. Accordingly, a component RPST may independently have properties of a tree, except that the RPST is part of a larger tree. Having properties of a tree, in a particular embodiment, a component RPST may comprise a finite, rooted, connected, unordered acyclic graph as illustrated with reference to
While a subtree and RPST of a full tree may represent portions of a graphical representation of the full tree and/or hierarchical data expressed in the full tree, properties of a subtree and RPST may be distinguished. In a particular embodiment, if the RPST comprises a child node coupled to the root node of the full tree, the RPST need not include all nodes and edges depending from the child node. Also, an RPST may comprise two or more child nodes connected to the root node of the full tree by respective edges. However, these are merely examples of properties that may distinguish an RPST from a subtree in a particular embodiment, and the claimed subject matter is not limited in this respect.
Since a tree is finite, there are a finite number of paths between a root node of the tree and any other node in the tree. Similarly, there are a finite number of combinations of paths between the root node of a tree and individual ones of the other nodes in the tree. Accordingly, in a particular embodiment, a finite number of RPSTs may be enumerated from a tree having a root node. Natural numerals may be associated with the enumerated RPSTs based, at least in part, on an association between trees and natural numerals such as, for example, illustrated above with reference to
According to an embodiment, the enumerated RPSTs of a tree may be represented as a “set” containing a collection of unordered elements. In a particular embodiment, the elements of the set of enumerated RPSTs may contain as elements natural numerals representing individual ones of the enumerated RPSTs according to the aforementioned association between trees and natural numerals. The elements of such a set may be alternatively expressed as graphical representations of the individual ones of the enumerated RPSTs. In a particular embodiment, a one-to-one mapping may relate elements of the set of RPSTs expressed as natural numerals and elements of the set of RPSTs expressed as graphical representations. Here, such a mapping may enable converting graphical representations of RPSTs to corresponding natural numerals and manipulation of such natural numerals to provide resulting natural numerals. The resulting natural numerals may then be converted back to graphical representations. However, these are merely examples of how a set of enumerated RPSTs may be expressed and the claimed subject matter is not limited in these respects.
For a particular embodiment, a “full tree” is defined as an integral tree comprising all of its nodes, edges coupling the nodes to one another and any labels associated with the nodes or edges. Therefore, a full tree includes all of its nodes and elements completely connected. Also, such a full tree may be represented by a natural numeral denoted here as “FT.” The notation “{RPSTs::FT}” provides a shorthand notation for this particular embodiment to indicate the set of unique, unordered RPSTs that may be formed from a full tree “FT,” In one embodiment, the elements of {RPSTs::FT} may comprise natural numerals representing corresponding component RPSTs. As shown in
According to an embodiment, the process 1250 recognizes that the full tree may represent any one of four different configurations: an empty tree; a single node tree; a tree comprising a single subtree connected to a root node of the full tree by an edge; and two or more subtrees connected to the root node of the full tree by respective edges. Accordingly, the process 1250 enumerates the RPSTs of the full tree based, at least in part, on the particular configuration of the full tree. Diamond 1256 determines whether FT represents an empty tree containing no nodes. If so, {RPSTs::FT} remains defined as the empty set and process 1250 terminates at block 1268. If diamond 1258 determines that FT contains a single node tree, block 1260 updates {RPSTs::FT} to include a natural numeral expressing a single node tree (here, {r}).
At diamond 1262 through block 1268, process 1250 enumerates RPSTs based, at least in part, on the configuration of the full tree as having either a single subtree connected to the root node of the full tree by an edge, or two or more subtrees connected to the root node by respective edges. If FT represents a single subtree connected to the root node of the full tree by an edge, block 1264 enumerates the RPSTs of the single subtree. Here, the RPSTs of the full tree may be determined, at least in part, from the RPSTs of the single subtree.
If FT represents a full tree having two or more subtrees connected to the root node of the tree by respective edges, block 1266 may enumerate the RPSTs of the individual ones of the two or more subtrees. At least some of the RPSTs of the full tree may be determined, at least in part, from RPSTs of the individual subtrees. Block 1266 may then enumerate additional RPSTs of the full tree based, at least in part, combinations of the enumerated RPSTs merged at the root node of the full tree.
According to an embodiment, blocks 1264 and 1266 may be carried out by recursive execution of at least a portion of the process 1250. At block 1264, for example, the single subtree of the full tree may itself comprise two or more subtree children connected by respective edges to a node. Block 1264 may execute portions of block 1266 to enumerate the RPSTs of the subtree based, at least in part, on RPSTs enumerated from individual ones of the subtree children of the single subtree. Similarly, block 1266 may enumerate RPSTs of individual ones of the subtrees connected to the root node of the full tree by executing portions of block 1264.
As described below in connection with relation (1), a push operation may define a relationship between a subtree and a child tree of the subtree. As an association between trees and natural numerals may associate particular trees with natural numerals (e.g., as illustrated in
push(j,k,x)=P[kx+j−k+(2−r)], if j<k and k>0 (1)
where:
It should be understood that while the push operation of relation (1) is suitable for performing specific embodiments described herein, this push operation is merely an example of how a push operation may be performed and the claimed subject matter is not limited in this respect. Additionally, it should be noted that the value of “r” is selected based upon a particular association of natural numerals and trees according to an association embodiment. Here, such an association of natural numerals may define a particular natural numeral to represent a tree comprising a single node. In the association of natural numeral with trees of
It should also be noted that “j” (the actual computed label index value associating the root node with the pushed subtree) is a function of the specific values of “e” (the specific edge label) and “n” (the specific node label). In the particular case of a BELT, for example, there may be no node values such that “j”=“e”. The value of “k” (total number of possible index values) may be determined as function of the possibilities of values of “e” (edge label value) and “n” (node label value) and, in a particular embodiment, “k” may be determined as the number of possibilities for “e” multiplied by the number of possibilities for “n.” Again, in the particular case of a BELT, “k” equals the number of possibilities for the value “e” since there are no node labels.
The techniques described herein for enumerating RPSTs of a full tree may be applied to any particular type of tree. For illustration purposes, particular examples described herein are directed to enumerating RPSTs of a BELT. Accordingly, while it is understood that an actual computed index value associating the root node with the pushed subtree may be determined from node labels (having a value “n”) and/or edge labels (having a value “e”), for simplicity the remaining discussion will denote the actual computed label index value “j” as an edge label value of an edge connecting a root node of a tree to a pushed child tree.
In enumerating at least some RPSTs of a tree based, at least in part, on enumerated RPSTs of a subtree of the RPST, it may be useful to express a push operation on multiple RPSTs in a single push operation. In addition to applying a push operation to a tree having a value x, the push operation may be applied to multiple trees or tree elements of a set (here, an unordered collection of elements representing trees, RPSTs, subtrees and/or child trees of a subtree) in relation (2) as follows:
push[j,k,{a,b,c}]={push(j,k,a)}U{push(j,k,b)}U{push(j,k,c)} (2)
where a, b and c are numerical representations of tree elements in the pushed set. The result of the operation of relation (2) may be referred to as a “pushed set” of tree elements,
push(j,k,x)=P[2*2+0−2+2−1]=P[3]=5.
It should be understood, however, the application of the push operation of relation (1) a BELT as illustrated in
To enumerate RPSTs of a subtree of a full tree, it may be useful to determine a natural numeral associated with a child tree of the subtree based, at least in part, on a natural numeral associated with the subtree (the natural numerals being based, at least in part, on an association between trees and natural numerals). Like the push operation of relation (1), according to an embodiment, an “inverse push” operation may define a relationship between a subtree (e.g., a subtree of a parent full tree) and the child tree of the subtree (as illustrated in
push−1(r,k,ST)=<Child,j>
Child=Int[(P−1(ST)+k−(2−r))/k]; and
j=[P−1(ST)+k−(2−r)]modulo[k] (3)
where:
It should also be understood that the inverse push operation of relation (3) is merely an example of an inverse push operation used to determine a natural numeral associated with a child tree based, at least in part on a natural numeral associated with a parent subtree, and that the claimed subject matter is not limited in this respect. For example, for simplicity relation (3) assumes that information of a computed index value “j” associating the root node of the parent full tree and the child tree may be derived from edge label values in the absence of node label values (e.g., as in the case of a BELT). However, relation (3) may be expanded to apply to other non-BELT trees. Applied to the tree of
In the particular embodiment of an inverse push operation illustrated in relation (3), the inverse Kleene enumeration function, P−1(h), provides a result based upon ST (value of, or natural numeral associated with the subtree). Since the Kleene enumeration function generates non-composite natural numerals, the domain of P−1(h) may be limited to non-composite natural numerals. In connection with the association of natural numerals and trees illustrated with reference to
To enumerate at least some of the RPSTs of a full tree having two or more subtrees, it may be useful to determine combinations of RPSTs enumerated from the different subtrees. In the case of a full tree comprising two subtrees, in a particular example, individual elements of a first set of RPSTs of the full tree derived from a first subtree (denoted as “X” for the purposes of illustration) may be combined or merged with individual elements of a second set of RSPTs of the tree derived from a second subtree (denoted as “Y” for the purposes of illustration). Here, the elements of X and Y may represent individually enumerated RPSTs of the tree derived from the first and second subtrees, respectively. In a particular embodiment, the elements of X and Y may be represented as natural numerals associated with enumerated RPSTs derived from the respective first and second subtrees (according to an association of trees and natural numerals as illustrated in
According to one embodiment, a merger operation discussed above (e.g., for combining trees at their root nodes to provide a graphical and numerical expression of the resulting merged trees) may be expanded to create a set merger operation to include a merger among RPSTs (e.g., derived from different subtrees as illustrated above). Here, a member RPST of a first set merges with a member RPST of a second set to provide a member of a third, merged set containing the merged RPSTs as elements, for all members of both first and second sets. Regarding the aforementioned representation of the RPSTs as natural numerals, the set merger operation to merge sets X and Y may be expressed as follows:
where:
Diamond 1606 determines whether FT comprises two or more nodes by determining whether FT is greater than r. If so, block 1610 may initiate execution of process 1700 shown in
If FT is greater than r, diamond 1708 determines whether FT represents a tree comprising a single subtree (e.g. comprising a child tree pushed from the full tree node by an edge as shown in
Similar to the process 1250 illustrated above with reference to
If diamond 1708 determines that FT represents a tree comprising a single subtree, block 1710 executes an inverse push operation on FT as illustrated above in relation (3) to determine a natural numeral “child” representing the child tree coupled to the root node of the tree represented by FT (and edge label value “j” linking the root node with the child tree). At least some of the RPSTs of the tree represented by FT may be derived from RPSTs of the child tree determined at block 1710. Accordingly, block 1712 may recursively execute process 1700 to enumerate the RPSTs of the child tree ({RPSTs::child}). Here, the recursively executed process may apply the natural numeral “child” representing the child tree (e.g., as determined at block 1710) as the FT input value. Block 1714 then combines the single node tree represented by “r” with the set of enumerated RPSTs determined at block 1712. Block 1716 then performs a push operation according to relation (2) on the elements of this combined set {RPSTs::child} to complete the enumeration of the elements of {RPSTs::FT} in a pushed set with the edge label value “j” determined from the inverse push operation at block 1710.
If diamond 1708 determines that FT represents a tree comprising a root node that merges two or more subtrees, block 1718 may enumerate the elements of {RPSTs::FT} by executing a process 1800 shown in
A processing loop of blocks 1806 through 1816 incrementally factors the composite numeral FT into non-composite numerals “ST” representing individual subtrees merged at the root node of the tree represented by FT. Again, this particular embodiment includes an association between trees and natural numerals that associates composite natural numerals with trees merging two or more subtrees at a root node and associates non-composite numerals with trees having a root node coupled to a single pushed subtree; however, the claimed subject matter is not limited in scope to this particular embodiment. Here, block 1804 initializes a “remainder” as FT and block 1808 determines the non-composite numeral ST as the smallest non-composite factor of the remainder. If the remainder is decreased to below r, representing a single node tree in this particular embodiment), sequential execution returns to process 1700 at block 1818.
Through successive executions of the processing loop of blocks 1806 through 1816, block 1808 may sequentially factor the numeral FT into non-composite numerals representing subtrees of the tree represented by FT. According to a particular association embodiment, these non-composite numerals may represent individual ones of subtrees merged at a root node of the tree represented by FT. As at least a portion of the RPSTs of the tree represented by FT may be determined from the RSPTs of these subtrees, block 1810 may recursively execute the process 1700 to enumerate the RPSTs of the subtrees represented by the non-composite values ST determined at block 1808.
It should be observed that the elements of {RPSTs::FT} are derived from the RPSTs enumerated from individual subtrees (determined through loop iterations of block 1810). In addition to these elements, {RPSTs::FT} also includes merged combinations of RPSTs derived from RPSTs enumerated from different subtrees at block 1810 in different loop iterations. Through executions of the loop of block 1806 through 1816, block 1812 updates {RPSTs::FT}. By way of example, for the purpose of illustration, in an initial iteration of the loop, block 1812 may merely assign elements to {RPSTs::FT} (which is initialized as the empty set) to include the RPSTs enumerated at block 1810 from a first subtree of the tree represented by FT. In a second iteration of the loop, block 1810 enumerates RPSTs of a second subtree of the tree represented by FT. In addition to adding the enumerated RPSTs of the second subtree to {RPSTs::FT} (updated in the initial loop iteration to include RPSTs enumerated from the first subtree), block 1812 in the second iteration also updates {RPSTs::FT} to include RPSTs formed from the merger of the current individual elements of {RPSTs::FT} (again, updated from the initial iteration) with individual enumerated RPSTs of the second subtree. Here, block 1812 employs a set merger operation according to relation (4) to determine a merger of the current individual elements of {RPSTs::FT} (e.g., assigning the elements of {RPSTs::FT} to “X”) with the individual elements of the enumerated RPSTs of the second subtree (e.g., assigning the elements of RPSTs of the second subtree to “Y”). Subsequent iterations of the processing loop of blocks 1806 through 1816 may then enumerate the RPSTs of additional subtrees, and update {RPSTs::FT} based upon the elements of {RPSTs::FT} updated in the previous iteration and the enumerated RPSTs of the subsequent subtree children in like fashion.
Tree 1900 may be represented as a natural numeral “249” according to an association of trees and natural numerals as described above with reference to
Block 1704 initializes {RPSTs::249} as an empty set to be subsequently filled with natural numerals representing RPSTs of tree 1900. Since 249 (here, FT) comprises a composite natural numeral, block 1718 may initiate an instance of process 1800. Block 1804 initializes “remainder”=249 and block 1808 determines ST to be the natural numeral 3 (since 249 may be factored into two non-composite numerals 3 and 83).
Block 1810 may initiate a first recursive instance of process 1700 while providing FT=ST=3 as an input value, diamond 1708 determines that 3 is a non-composite numeral. Block 1710 performs an inverse push operation according to relation (3) to determine a natural numeral representative of the child tree of the subtree corresponding to the natural numeral 3 and an edge label value of an edge linking the child tree with the root node as follows:
Block 1712 initiates execution of a second recursive instance of process 1700, initializing {RPSTs::child}=Ø and terminating at block 1720 through diamond 1706 (since child=1≤r). Returning to block 1714 of the first recursive instance of process 1700, {RPSTs::child} is updated to be {r}={1} for this particular case of a BELT. Block 1716 then performs a push operation on the elements of the set {r} according to relation (2) (applying the edge label value=1 as determined in relation (5) for block 1710) to provide an RPST, {3}, which is graphically illustrated in
Execution of the initial instance of process 1800 then returns to block 1812 for updating {RPSTs::FT} by including {RPSTs::ST} (={3} as determined above) and merged combinations of the enumerated {RPSTs::ST} with any other previously enumerated RPSTs according to relation (4). Since {RPSTs::FT} at this point comprises an empty set, block 1812 merely updates {RPSTs::FT} to include the single element of {RPSTs::ST}. Block 1814 updates the remainder as FT/ST=249/3=83. This numeral corresponds to a subtree of tree 1900 formed by nodes 1902, 1906, 1908, 1910 and 1912 graphically illustrated as subtree 2100 in
On a second iteration of the processing loop of blocks 1806 through 1816, block 1808 determines the non-composite factor of the remainder updated at block 1814 of the first iteration of the processing loop. Here, the natural numeral remainder, 83 as determined at block 1814 in the first iteration, comprises a non-composite numeral. Accordingly, block 1808 determines the natural numeral ST of the current iteration to be 83. Block 1810 then determines {RPSTs::83} by initiating a third recursive instance of process 1700. Since 83 is a non-composite natural numeral (as determined at diamond 1708), block 1710 determines the inverse push of 83 according to relation (3) as follows:
The result of this inverse push operation is graphically illustrated in
Block 1712 may initiate a sixth recursive instance of process 1700 to determine {RPSTs::1}. Diamond 1706 of the sixth recursive instance of process 1700 may terminate and return {RPSTs::1}=Ø (i.e., the empty set). Returning to the fifth recursive instance of process 1700, block 1714 updates {RPSTs::child} to include {r} ({r}={1} for this particular case where tree 1200 is a BELT). Accordingly, {RPSTs::2}=push {1}={2} (using the edge label value)=0 as determined at block 1710 of the fifth recursive instance of process 1700 and shown in relation (7)). This corresponds with the RPST 2300 of child tree 2200 formed by node 1906, and either node 1908 or 1912 as shown in
Returning to block 1812 of the first recursive instance of process 1800, {RPSTs::12} is updated as {2}. The remainder is updated to be the natural numeral remainder/ST 12/2=6. Block 1808 determines ST to be the smallest non-composite factor of the updated remainder (here, “6”) to be “2.” As illustrated above in the fifth recursive instance of process 1700, block 1810 determines {RPSTs::2} to be {2} (again, corresponding with the RPST of subtree 2200 formed by node 1906, and either node 1908 or 1912). Block 1812 may then determine combinations of the previously enumerated elements of {RPSTs::12} with the elements of {RPSTs::ST} using the set merger operation of relation (4) and update {RPSTs::12} as follows:
This updated {RPSTs::12} is graphically illustrated in
Block 1814 then updates the remainder=remainder/ST=6/2=3, and the next iteration of the processing loop of blocks 1806 through 1816 determines ST as “3” at block 1808. Block 1810 may determine {RPSTs::ST}={RPSTs::=3}={3} as illustrated above in the first recursive instance of process 1700. This resulting RSPT of the child tree 2200 includes nodes 1906 and 1910 as shown in RPST 2500 of
The resulting elements of {RPSTs::12} are graphically illustrated in
Returning to the third recursive instance of process 1700 (following the identification of 2200 as the child tree of RPST 2100 at block 1710 and the enumeration of the RPSTs of subtree 2200 as the elements of {RPSTs::12} in block 1712}), block 1714 updates {RPSTs::child} to include {RPSTs::12} U {r}={1, 2, 3, 4, 6, 12}. Block 1716 may then complete the enumeration of the elements of {RPSTs::83} by performing a push operation on the elements of {RPSTs::child} according to relation (2) (with label index value j=0 as determined in relation (6)) as follows:
{RPSTs::83}=zero-push({1,2,3,4,0,12})={2,5,11,17,31,83} (10)
The resulting elements of {RPSTs::83} are graphically illustrated with reference to
Returning to the initial instance of process 1800 (following the enumeration of elements in {RPSTs::3} corresponding with a first subtree merged at root node 1902 as graphically illustrated in
While the above illustrated example is a specific case of enumerating RPSTs from one particular BELT (associated with the natural numeral 249), it should be understood that the processes are general enough to enumerate RPSTs for any tree. Also, while the illustrated example is specifically directed to enumerating RPSTS of a BELT, the claimed subject matter is not limited to this specific example or specifically to BELTs.
According to an embodiment, the technique described above may have many applications in the management and/or manipulation of hierarchical data. The ability to enumerate possible RPSTs from a tree may be applied to any one of several database management applications. In one example, a complicated tree matching process may be simplified to a more computationally efficient set inclusion process. In a particular example, processing a query to an extensible markup language (XML) document or set of documents may be simplified to a set inclusion process. Here, the XML document or set of documents may be represented as a tree associated with a natural numeral. The RPSTs of the tree may then be enumerated to model possible logical branches of the query through the XML document or set of documents, and enumerated RPSTs are associated with natural numerals in a set of natural numerals representing the possible logical branches. A natural numeral representing the query may then be compared with the elements in the set representing the possible logical branches to determine one or more matches. The query may then be “answered” using the RPSTs associated with the matched elements.
In another particular example applied to biometric pattern recognition, a known biometric pattern (e.g., facial features) may be modeled as a tree associated with a natural numeral. The RPSTs of the tree may then be enumerated to model possible features or combinations of features of the biometric pattern, and the enumerated RPSTs may be associated with natural numerals in a set of natural numerals representing features of the biometric pattern. A natural numeral representing one or more detected features of a subject or specimen may be compared to the elements of the set to determine one or more matches. A positive identification of the subject or specimen may then be determined based, at least in part, upon the one or more matches.
It should be understood that the above described applications of the process for enumerating RPSTs of a tree are merely example applications and that the claimed subject matter is not limited to such example applications.
It should also be understood that, although particular embodiments have just been described, the claimed subject matter is not limited in scope to a particular embodiment or implementation. For example, one embodiment may be in hardware, such as implemented to operate on a device or combination of devices, for example, whereas another embodiment may be in software. Likewise, an embodiment may be implemented in firmware, or as any combination of hardware, software, and/or firmware, for example. Such software and/or firmware may be expressed as machine-readable instructions which are executable by a processor. Likewise, although the claimed subject matter is not limited in scope in this respect, one embodiment may comprise one or more articles, such as a storage medium or storage media. This storage media, such as one or more CD-ROMs and/or disks, for example, may have stored thereon instructions, that when executed by a system, such as a computer system, computing platform, or other system, for example, may result in an embodiment of a method in accordance with the claimed subject matter being executed, such as one of the embodiments previously described for example. As one potential example, a computing platform may include one or more processing units or processors, one or more input/output devices, such as a display, a keyboard and/or a mouse, and/or one or more memories, such as static random access memory, dynamic random access memory, flash memory, and/or a hard drive, although, again, the claimed subject matter is not limited in scope to this example.
In the preceding description, various aspects of the claimed subject matter have been described. For purposes of explanation, specific numbers, systems and/or configurations were set forth to provide a thorough understanding of the claimed subject matter. However, it should be apparent to one skilled in the art having the benefit of this disclosure that the claimed subject matter may be practiced without the specific details. In other instances, well-known features were omitted and/or simplified so as not to obscure the claimed subject matter. While certain features have been illustrated and/or described herein, many modifications, substitutions, changes and/or equivalents will now occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and/or changes as fall within the true spirit of the claimed subject matter.
Number | Name | Date | Kind |
---|---|---|---|
3201701 | Maitra | Aug 1965 | A |
3704345 | Cecil et al. | Nov 1972 | A |
4001951 | Fasse | Jan 1977 | A |
4134218 | Adams et al. | Jan 1979 | A |
4156910 | Barton et al. | May 1979 | A |
4286330 | Isaacson | Aug 1981 | A |
4439162 | Blaine | Mar 1984 | A |
4677550 | Ferguson | Jun 1987 | A |
4737109 | Abramson | Apr 1988 | A |
4745561 | Hirosawa et al. | May 1988 | A |
4751684 | Holt | Jun 1988 | A |
4831525 | Saito et al. | May 1989 | A |
4867686 | Goldstein | Sep 1989 | A |
4905138 | Bourne | Feb 1990 | A |
4916655 | Ohsone et al. | Apr 1990 | A |
4931928 | Greenfeld | Jun 1990 | A |
4949388 | Bhaskaran | Aug 1990 | A |
4989132 | Mellender et al. | Jan 1991 | A |
4991087 | Burkowski et al. | Feb 1991 | A |
5010478 | Deran | Apr 1991 | A |
5021943 | Grimes | Jun 1991 | A |
5021992 | Kondo | Jun 1991 | A |
5050071 | Harris et al. | Sep 1991 | A |
5136593 | Moon et al. | Aug 1992 | A |
5191522 | Bosco et al. | Mar 1993 | A |
5235701 | Ohler et al. | Aug 1993 | A |
5265245 | Nordstrom et al. | Nov 1993 | A |
5295261 | Simonetti | Mar 1994 | A |
5325531 | McKeeman et al. | Jun 1994 | A |
5335320 | Iwata et al. | Aug 1994 | A |
5335345 | Frieder et al. | Aug 1994 | A |
5355496 | Fant et al. | Oct 1994 | A |
5450581 | Bergen et al. | Sep 1995 | A |
5463777 | Bialkowski et al. | Oct 1995 | A |
5493504 | Minato | Feb 1996 | A |
5493678 | Arcuri et al. | Feb 1996 | A |
5497500 | Rogers et al. | Mar 1996 | A |
5509088 | Robson | Apr 1996 | A |
5511159 | Baker et al. | Apr 1996 | A |
5519627 | Mahmood et al. | May 1996 | A |
5522068 | Berkowitz | May 1996 | A |
5544301 | Orton et al. | Aug 1996 | A |
5548755 | Leung et al. | Aug 1996 | A |
5577253 | Blickstein | Nov 1996 | A |
5590319 | Cohen et al. | Dec 1996 | A |
5598350 | Kawanishi et al. | Jan 1997 | A |
5606669 | Bertin et al. | Feb 1997 | A |
5636155 | Kabuo | Jun 1997 | A |
5687362 | Bhargava et al. | Nov 1997 | A |
5701461 | Dalal et al. | Dec 1997 | A |
5706406 | Pollock | Jan 1998 | A |
5724512 | Winterbottom | Mar 1998 | A |
5724576 | Letourneau | Mar 1998 | A |
5742806 | Reiner et al. | Apr 1998 | A |
5745892 | Miyata et al. | Apr 1998 | A |
5748975 | LeTourneau | May 1998 | A |
5758152 | Letourneau | May 1998 | A |
5778354 | Leslie et al. | Jul 1998 | A |
5778371 | Fujihara | Jul 1998 | A |
5781906 | Aggarwal et al. | Jul 1998 | A |
5784557 | Oprescu | Jul 1998 | A |
5787415 | Jacobson et al. | Jul 1998 | A |
5787432 | Letourneau | Jul 1998 | A |
5796356 | Okada et al. | Aug 1998 | A |
5802370 | Sitbon et al. | Sep 1998 | A |
5822593 | Lamping et al. | Oct 1998 | A |
5826262 | Bui et al. | Oct 1998 | A |
5838319 | Guzak et al. | Nov 1998 | A |
5848159 | Collins et al. | Dec 1998 | A |
5905138 | Van Broekhoven | May 1999 | A |
5930805 | Marquis | Jul 1999 | A |
5937181 | Godefroid et al. | Aug 1999 | A |
5940619 | Abadi et al. | Aug 1999 | A |
5960425 | Buneman et al. | Sep 1999 | A |
5970490 | Morgenstern | Oct 1999 | A |
5978790 | Buneman et al. | Nov 1999 | A |
5987449 | Suciu | Nov 1999 | A |
5999926 | Suciu | Dec 1999 | A |
6002879 | Radigan et al. | Dec 1999 | A |
6003033 | Amano et al. | Dec 1999 | A |
6022879 | Crow et al. | Feb 2000 | A |
6028987 | Hirairi | Feb 2000 | A |
6055537 | Letourneau | Apr 2000 | A |
6076087 | Suciu | Jun 2000 | A |
6088691 | Bhargava et al. | Jul 2000 | A |
6141655 | Johnson et al. | Oct 2000 | A |
6199059 | Dahan et al. | Mar 2001 | B1 |
6199103 | Sakaguchi et al. | Mar 2001 | B1 |
6236410 | Politis et al. | May 2001 | B1 |
6240418 | Shadmon | May 2001 | B1 |
6243859 | Chen-Kuang | Jun 2001 | B1 |
6272495 | Hetherington | Aug 2001 | B1 |
6279007 | Uppala | Aug 2001 | B1 |
6289354 | Aggarwal et al. | Sep 2001 | B1 |
6292938 | Sarkar et al. | Sep 2001 | B1 |
6314559 | Sollich | Nov 2001 | B1 |
6336812 | Cooper et al. | Jan 2002 | B1 |
6341372 | Datig | Jan 2002 | B1 |
6377953 | Gawlick et al. | Apr 2002 | B1 |
6411957 | Dijkstra | Jun 2002 | B1 |
6438540 | Nasr et al. | Aug 2002 | B2 |
6442584 | Kolli et al. | Aug 2002 | B1 |
6446256 | Hyman et al. | Sep 2002 | B1 |
6466240 | Maslov | Oct 2002 | B1 |
6480857 | Chandler | Nov 2002 | B1 |
6499036 | Gurevich | Dec 2002 | B1 |
6505205 | Kothuri et al. | Jan 2003 | B1 |
6542899 | Saulpaugh et al. | Apr 2003 | B1 |
6550024 | Pagurek et al. | Apr 2003 | B1 |
6556983 | Altschuler et al. | Apr 2003 | B1 |
6598052 | Saulpaugh et al. | Jul 2003 | B1 |
6598502 | Rosa | Jul 2003 | B1 |
6606632 | Saulpaugh et al. | Aug 2003 | B1 |
6606741 | Kojima et al. | Aug 2003 | B2 |
6609130 | Saulpaugh et al. | Aug 2003 | B1 |
6610106 | Jenks | Aug 2003 | B1 |
6611844 | Saulpaugh et al. | Aug 2003 | B1 |
6640218 | Golding et al. | Oct 2003 | B1 |
6654734 | Mani et al. | Nov 2003 | B1 |
6658649 | Bates et al. | Dec 2003 | B1 |
6665664 | Paulley et al. | Dec 2003 | B2 |
6687734 | Sellink et al. | Feb 2004 | B1 |
6691301 | Bowen | Feb 2004 | B2 |
6708164 | Cseri et al. | Mar 2004 | B1 |
6714939 | Saldanha et al. | Mar 2004 | B2 |
6728953 | Walster | Apr 2004 | B1 |
6742054 | Upton, IV | May 2004 | B1 |
6745384 | Biggerstaff | Jun 2004 | B1 |
6748378 | Lavender et al. | Jun 2004 | B1 |
6763515 | Vazquez et al. | Jul 2004 | B1 |
6785673 | Fernandez et al. | Aug 2004 | B1 |
6785685 | Soetarman et al. | Aug 2004 | B2 |
6795868 | Dingman et al. | Sep 2004 | B1 |
6804677 | Shadmon et al. | Oct 2004 | B2 |
6817865 | Charbonneau | Nov 2004 | B2 |
6829695 | Ross | Dec 2004 | B1 |
6847979 | Allemang et al. | Jan 2005 | B2 |
6854976 | Suhr | Feb 2005 | B1 |
6874005 | Fortenberry et al. | Mar 2005 | B2 |
6880148 | Raph et al. | Apr 2005 | B1 |
6941511 | Hind et al. | Sep 2005 | B1 |
6950815 | Tijare et al. | Sep 2005 | B2 |
6965990 | Barsness et al. | Nov 2005 | B2 |
6968330 | Edwards et al. | Nov 2005 | B2 |
6978271 | Hoffman et al. | Dec 2005 | B1 |
7043555 | McClain et al. | May 2006 | B1 |
7051033 | Agarwal et al. | May 2006 | B2 |
7072904 | Najork et al. | Jul 2006 | B2 |
7103838 | Krishnamurthy et al. | Sep 2006 | B1 |
7107265 | Calvignac et al. | Sep 2006 | B1 |
7111016 | Gurevich | Sep 2006 | B2 |
7117196 | Gaur et al. | Oct 2006 | B2 |
7117479 | Vanter | Oct 2006 | B2 |
7120645 | Manikutty et al. | Oct 2006 | B2 |
7127704 | Vanter et al. | Oct 2006 | B2 |
7134075 | Hind et al. | Nov 2006 | B2 |
7139765 | Balkany | Nov 2006 | B1 |
7140006 | Harrison, III et al. | Nov 2006 | B2 |
7162485 | Gottlob et al. | Jan 2007 | B2 |
7167856 | Lawder | Jan 2007 | B2 |
7190376 | Tonisson | Mar 2007 | B1 |
7191182 | Anonsen et al. | Mar 2007 | B2 |
7203680 | Parida | Apr 2007 | B2 |
7203774 | Zhou et al. | Apr 2007 | B1 |
7210097 | Clarke et al. | Apr 2007 | B1 |
7225183 | Gardner | May 2007 | B2 |
7225199 | Green et al. | May 2007 | B1 |
7263525 | Shin | Aug 2007 | B2 |
7287026 | Oommen | Oct 2007 | B2 |
7313563 | Bordawekar et al. | Dec 2007 | B2 |
7318066 | Kaufman et al. | Jan 2008 | B2 |
7318215 | Krishnan et al. | Jan 2008 | B1 |
7337163 | Srinivasan et al. | Feb 2008 | B1 |
7356802 | Sutter et al. | Apr 2008 | B2 |
7360202 | Seshadri et al. | Apr 2008 | B1 |
7386541 | Pal et al. | Jun 2008 | B2 |
7392239 | Fontoura et al. | Jun 2008 | B2 |
7403940 | Narsude | Jul 2008 | B2 |
7409673 | Kuo et al. | Aug 2008 | B2 |
7419376 | Sarvazyan et al. | Sep 2008 | B2 |
7421648 | Davis | Sep 2008 | B1 |
7437666 | Ramarao et al. | Oct 2008 | B2 |
7475070 | Fan et al. | Jan 2009 | B2 |
7478100 | Murthy et al. | Jan 2009 | B2 |
7493305 | Thusoo et al. | Feb 2009 | B2 |
7496892 | Nuss | Feb 2009 | B2 |
7512932 | Davidov et al. | Mar 2009 | B2 |
7536675 | Gallagher | May 2009 | B2 |
7536676 | Baker et al. | May 2009 | B2 |
7544062 | Hauschild et al. | Jun 2009 | B1 |
7561927 | Oyama et al. | Jul 2009 | B2 |
7571156 | Gupta et al. | Aug 2009 | B1 |
7571169 | Jones et al. | Aug 2009 | B2 |
7574692 | Herscu | Aug 2009 | B2 |
7575434 | Palakodeti | Aug 2009 | B2 |
7620632 | Andrews | Nov 2009 | B2 |
7627591 | Letourneau | Dec 2009 | B2 |
7630995 | Letourneau | Dec 2009 | B2 |
7636727 | Schiffmann | Dec 2009 | B2 |
7650592 | Eckels et al. | Jan 2010 | B2 |
7669183 | Bowman et al. | Feb 2010 | B2 |
7681177 | Letourneau | Mar 2010 | B2 |
7685137 | Liu et al. | Mar 2010 | B2 |
7720830 | Wen et al. | May 2010 | B2 |
7761847 | Kornerup et al. | Jul 2010 | B2 |
7761858 | Chang et al. | Jul 2010 | B2 |
7765183 | Williams, Jr. | Jul 2010 | B2 |
7779396 | Meijer et al. | Aug 2010 | B2 |
7792866 | Linden et al. | Sep 2010 | B2 |
7801923 | Letourneau | Sep 2010 | B2 |
7809758 | Thurnhofer et al. | Oct 2010 | B2 |
7827523 | Ahmed et al. | Nov 2010 | B2 |
7861304 | Nachenberg et al. | Dec 2010 | B1 |
7882147 | Letourneau | Feb 2011 | B2 |
7890471 | Fan et al. | Feb 2011 | B2 |
7890927 | Eldridge et al. | Feb 2011 | B2 |
7890928 | Patrudu | Feb 2011 | B2 |
7899821 | Schiffmann et al. | Mar 2011 | B1 |
7962494 | Furusho | Jun 2011 | B2 |
8005869 | Corl, Jr. et al. | Aug 2011 | B2 |
8020145 | Fant | Sep 2011 | B2 |
8032828 | Su et al. | Oct 2011 | B2 |
8032860 | Piehler et al. | Oct 2011 | B2 |
8037102 | Letourneau | Oct 2011 | B2 |
8060868 | Meijer et al. | Nov 2011 | B2 |
8086998 | Bansal et al. | Dec 2011 | B2 |
8112740 | Meijer et al. | Feb 2012 | B2 |
8151276 | Grechanik et al. | Apr 2012 | B2 |
8181155 | Pinto et al. | May 2012 | B2 |
8203972 | Sauermann | Jun 2012 | B2 |
8230526 | Holland et al. | Jul 2012 | B2 |
8250526 | Anderson et al. | Aug 2012 | B2 |
8290977 | Chinchwadkar et al. | Oct 2012 | B2 |
8307102 | Skog | Nov 2012 | B2 |
8316059 | Schiffmann et al. | Nov 2012 | B1 |
8321478 | Fong | Nov 2012 | B2 |
8332428 | Bonneau et al. | Dec 2012 | B2 |
8356040 | Letourneau | Jan 2013 | B2 |
8365137 | Fant | Jan 2013 | B2 |
8438534 | Thomson et al. | May 2013 | B2 |
8443339 | Letourneau | May 2013 | B2 |
8447774 | Robie et al. | May 2013 | B1 |
8458191 | Bhattacharjee et al. | Jun 2013 | B2 |
8484236 | Andrews et al. | Jul 2013 | B1 |
8606794 | Amer-Yahia et al. | Dec 2013 | B2 |
8612461 | Schiffmann et al. | Dec 2013 | B2 |
8615530 | Letourneau | Dec 2013 | B1 |
8626777 | Letourneau | Jan 2014 | B2 |
8645346 | Dumitru et al. | Feb 2014 | B2 |
8650201 | Letourneau | Feb 2014 | B2 |
8683431 | Thomson et al. | Mar 2014 | B2 |
8745070 | Krishnamurthy et al. | Jun 2014 | B2 |
8762942 | Langworthy et al. | Jun 2014 | B2 |
8868621 | D'Onofrio et al. | Oct 2014 | B2 |
8869106 | Jazdzewski et al. | Oct 2014 | B2 |
8930896 | Wiggins | Jan 2015 | B1 |
8935232 | Abadi et al. | Jan 2015 | B2 |
8990769 | Letourneau | Mar 2015 | B2 |
9002862 | Schiffmann et al. | Apr 2015 | B2 |
9015202 | Letourneau | Apr 2015 | B2 |
9020961 | Letoruneau et al. | Apr 2015 | B2 |
9043347 | Letourneau | May 2015 | B2 |
9077515 | Letourneau | Jul 2015 | B2 |
9167579 | Fettweis et al. | Oct 2015 | B2 |
9177003 | Letourneau | Nov 2015 | B2 |
9245050 | Schiffmann et al. | Jan 2016 | B2 |
9330128 | Schiffmann | May 2016 | B2 |
9411841 | Schiffmann et al. | Aug 2016 | B2 |
9425951 | Letourneau et al. | Aug 2016 | B2 |
9430512 | Letourneau et al. | Aug 2016 | B2 |
9563653 | Letourneau et al. | Feb 2017 | B2 |
9563663 | Shukla et al. | Feb 2017 | B2 |
9646034 | Schiffmann et al. | May 2017 | B2 |
9646107 | Letourneau et al. | May 2017 | B2 |
9842130 | Schiffmann et al. | Dec 2017 | B2 |
10055438 | Schiffmann et al. | Aug 2018 | B2 |
10068003 | Letourneau | Sep 2018 | B2 |
10140349 | Letourneau | Nov 2018 | B2 |
10255311 | Letourneau | Apr 2019 | B2 |
10275489 | Reddy et al. | Apr 2019 | B1 |
10325031 | Letourneau | Jun 2019 | B2 |
10380039 | Cooray et al. | Aug 2019 | B2 |
10380089 | Letourneau | Aug 2019 | B2 |
10394785 | Letourneau | Aug 2019 | B2 |
10411878 | Letourneau | Sep 2019 | B2 |
10437886 | Andrews et al. | Oct 2019 | B2 |
10713274 | Letourneau | Jul 2020 | B2 |
10725989 | Schiffmann et al. | Jul 2020 | B2 |
10733234 | Letourneau | Aug 2020 | B2 |
11100070 | Schiffmann et al. | Aug 2021 | B2 |
11100137 | Letourneau | Aug 2021 | B2 |
11194777 | Schiffmann et al. | Dec 2021 | B2 |
11204906 | Letourneau | Dec 2021 | B2 |
11663238 | LeTourneau | May 2023 | B2 |
20010003211 | Bera | Jun 2001 | A1 |
20010037496 | Simonyi | Nov 2001 | A1 |
20020023166 | Bar-Noy et al. | Feb 2002 | A1 |
20020040292 | Marcu | Apr 2002 | A1 |
20020059281 | Watanabe et al. | May 2002 | A1 |
20020062259 | Katz et al. | May 2002 | A1 |
20020091676 | Agrawal et al. | Jul 2002 | A1 |
20020107860 | Gobeille | Aug 2002 | A1 |
20020129129 | Bloch et al. | Sep 2002 | A1 |
20020130796 | Tsuchido et al. | Sep 2002 | A1 |
20020130907 | Chi et al. | Sep 2002 | A1 |
20020133347 | Schoneburg et al. | Sep 2002 | A1 |
20020133497 | Draper et al. | Sep 2002 | A1 |
20020149604 | Wilkinson | Oct 2002 | A1 |
20020169563 | Ferreira | Nov 2002 | A1 |
20020194163 | Hopeman et al. | Dec 2002 | A1 |
20030041088 | Wilson et al. | Feb 2003 | A1 |
20030065659 | Agarwal et al. | Apr 2003 | A1 |
20030074436 | Gieseke | Apr 2003 | A1 |
20030115559 | Sawada | Jun 2003 | A1 |
20030130977 | Oommen | Jul 2003 | A1 |
20030149934 | Worden | Aug 2003 | A1 |
20030167445 | Su et al. | Sep 2003 | A1 |
20030195885 | Emmick et al. | Oct 2003 | A1 |
20030195890 | Oommen | Oct 2003 | A1 |
20030236787 | Burges | Dec 2003 | A1 |
20030236794 | Hostetter et al. | Dec 2003 | A1 |
20040003028 | Emmett et al. | Jan 2004 | A1 |
20040010752 | Chan et al. | Jan 2004 | A1 |
20040019599 | Trappen et al. | Jan 2004 | A1 |
20040024724 | Rubin | Feb 2004 | A1 |
20040024790 | Everett | Feb 2004 | A1 |
20040044659 | Judd et al. | Mar 2004 | A1 |
20040054692 | Seyrat et al. | Mar 2004 | A1 |
20040060006 | Lindblad et al. | Mar 2004 | A1 |
20040060007 | Gottlob et al. | Mar 2004 | A1 |
20040068498 | Patchet et al. | Apr 2004 | A1 |
20040073541 | Lindblad et al. | Apr 2004 | A1 |
20040075677 | Loyall et al. | Apr 2004 | A1 |
20040103105 | Lindblad et al. | May 2004 | A1 |
20040122844 | Malloy et al. | Jun 2004 | A1 |
20040125124 | Kim et al. | Jul 2004 | A1 |
20040160464 | Reyna | Aug 2004 | A1 |
20040205047 | Carpenter | Oct 2004 | A1 |
20040215642 | Cameron et al. | Oct 2004 | A1 |
20040239674 | Ewald et al. | Dec 2004 | A1 |
20040254909 | Testa | Dec 2004 | A1 |
20040260683 | Chan et al. | Dec 2004 | A1 |
20040260684 | Agrawal et al. | Dec 2004 | A1 |
20040267958 | Reed et al. | Dec 2004 | A1 |
20040268236 | Chidlovskii et al. | Dec 2004 | A1 |
20050021548 | Bohannon et al. | Jan 2005 | A1 |
20050021683 | Newton et al. | Jan 2005 | A1 |
20050023524 | Beatty | Feb 2005 | A1 |
20050027495 | Matichuk | Feb 2005 | A1 |
20050027743 | O'Neil et al. | Feb 2005 | A1 |
20050028091 | Bordawekar et al. | Feb 2005 | A1 |
20050050016 | Stanoi et al. | Mar 2005 | A1 |
20050050066 | Hughes | Mar 2005 | A1 |
20050055369 | Gorelik et al. | Mar 2005 | A1 |
20050058976 | Vernon | Mar 2005 | A1 |
20050060320 | Bostrom | Mar 2005 | A1 |
20050060332 | Bernstein et al. | Mar 2005 | A1 |
20050065964 | Ziemann et al. | Mar 2005 | A1 |
20050065965 | Ziemann et al. | Mar 2005 | A1 |
20050097084 | Balmin et al. | May 2005 | A1 |
20050102636 | Mckeon et al. | May 2005 | A1 |
20050125432 | Lin et al. | Jun 2005 | A1 |
20050138073 | Zhou et al. | Jun 2005 | A1 |
20050149471 | Lassalle | Jul 2005 | A1 |
20050154265 | Miro et al. | Jul 2005 | A1 |
20050154979 | Chidlovskii et al. | Jul 2005 | A1 |
20050156761 | Oh | Jul 2005 | A1 |
20050165732 | Burges | Jul 2005 | A1 |
20050171962 | Martin et al. | Aug 2005 | A1 |
20050187900 | LeTourneau | Aug 2005 | A1 |
20050195741 | Doshi et al. | Sep 2005 | A1 |
20050210014 | Asano | Sep 2005 | A1 |
20050214727 | Stoianovici et al. | Sep 2005 | A1 |
20050216445 | Rao | Sep 2005 | A1 |
20050267908 | LeTourneau | Dec 2005 | A1 |
20050286788 | Orr | Dec 2005 | A1 |
20050289125 | Liu et al. | Dec 2005 | A1 |
20060004817 | Andrews | Jan 2006 | A1 |
20060005122 | Lemoine | Jan 2006 | A1 |
20060015538 | LeTourneau | Jan 2006 | A1 |
20060053122 | Korn et al. | Mar 2006 | A1 |
20060074838 | Srivastava | Apr 2006 | A1 |
20060095442 | LeTourneau | May 2006 | A1 |
20060095455 | LeTourneau | May 2006 | A1 |
20060123029 | LeTourneau | Jun 2006 | A1 |
20060129582 | Schiffmann et al. | Jun 2006 | A1 |
20060209351 | Saito | Sep 2006 | A1 |
20060259533 | LeTourneau | Nov 2006 | A1 |
20060271573 | LeTourneau | Nov 2006 | A1 |
20070003917 | Kitching et al. | Jan 2007 | A1 |
20070198538 | Palacios | Aug 2007 | A1 |
20080270435 | Furusho | Oct 2008 | A1 |
20080313196 | Furusho | Dec 2008 | A1 |
20100094885 | Andrews | Apr 2010 | A1 |
20100094908 | Letourneau | Apr 2010 | A1 |
20100114969 | Letourneau | May 2010 | A1 |
20100191775 | Schiffmann et al. | Jul 2010 | A1 |
20100205581 | Letourneau | Aug 2010 | A1 |
20100318521 | Letourneau | Dec 2010 | A1 |
20110131259 | Letourneau | Jun 2011 | A1 |
20110282898 | Schiffmann et al. | Nov 2011 | A1 |
20110320499 | Letourneau | Dec 2011 | A1 |
20120144388 | Kurian et al. | Jun 2012 | A1 |
20130151566 | Schiffmann et al. | Jun 2013 | A1 |
20130198239 | LeToruneau | Aug 2013 | A1 |
20140040293 | Letourneau | Feb 2014 | A1 |
20140184430 | Jiang et al. | Jul 2014 | A1 |
20140289266 | Letourneau | Sep 2014 | A1 |
20140289278 | Schiffmann et al. | Sep 2014 | A1 |
20140289279 | Letourneau | Sep 2014 | A1 |
20140362961 | Letourneau | Dec 2014 | A1 |
20150193517 | Letourneau | Jul 2015 | A1 |
20150220582 | Letourneau | Aug 2015 | A1 |
20150242449 | Schiffmann et al. | Aug 2015 | A1 |
20150242450 | Letourneau | Aug 2015 | A1 |
20150310048 | Letourneau | Oct 2015 | A1 |
20150341165 | Letourneau | Nov 2015 | A1 |
20160117353 | Schiffmann et al. | Apr 2016 | A1 |
20160162528 | Letourneau | Jun 2016 | A1 |
20160283611 | Schiffmann et al. | Sep 2016 | A1 |
20160328431 | Schiffmann et al. | Nov 2016 | A1 |
20160359616 | Letourneau | Dec 2016 | A1 |
20170032053 | Letourneau | Feb 2017 | A1 |
20170053006 | Letourneau | Feb 2017 | A1 |
20170132301 | Letourneau | May 2017 | A1 |
20170255660 | Schiffmann et al. | Sep 2017 | A1 |
20180107698 | Schiffmann et al. | Apr 2018 | A1 |
20190026326 | Schiffmann et al. | Jan 2019 | A1 |
20190034510 | Letourneau | Jan 2019 | A1 |
20190121795 | Schiffmann et al. | Apr 2019 | A1 |
20190129899 | Letourneau | May 2019 | A1 |
20190171628 | Letourneau | Jun 2019 | A1 |
20190236078 | Letourneau | Aug 2019 | A1 |
20190356465 | Letourneau | Nov 2019 | A1 |
20190377718 | Letourneau | Dec 2019 | A1 |
20190384753 | Letourneau | Dec 2019 | A1 |
20190384792 | Andrews et al. | Dec 2019 | A1 |
20200218707 | Letourneau | Jul 2020 | A1 |
20200372041 | Letourneau | Nov 2020 | A1 |
20200394168 | Schiffmann et al. | Dec 2020 | A1 |
20200394224 | Letourneau | Dec 2020 | A1 |
20210149860 | Letourneau | May 2021 | A1 |
20210349871 | Letourneau | Nov 2021 | A1 |
Number | Date | Country |
---|---|---|
2004012083 | Feb 2004 | WO |
Entry |
---|
U.S. Pat. No. 7,386,541 (“Pal”), United States, Jun. 10, 2008. |
U.S. Pat. App. Pub. No. 2004/0073541 (“Lindblad”), United States, Apr. 15, 2004. |
U.S. Pat. No. 7,809,758 (“Thurnhofer”), United States, Oct. 5, 2010. |
Tree Representation of Positive Integers, 1994, Abe. |
A New Bijection between Natural Numbers and Rooted Trees, 2005, Cappello. |
An Algorithm for Subtree Identification, Apr. 1968, Matula. |
The Art of Computer Programming Second Edition vol. 1 Fundamental Algorithms, 1973, Knuth. |
Abe, Y. Tree Representation of Positive Integers, Applied Mathematics Letters vol. 7 No. 1, Jan. 1994, p. 57. |
Cappello, Peter R., A New Bijection between Natural Numbers and Rooted Trees, Department of Computer Science, 2005, pp. 1-10. |
Grimm, Tralics a LaTeX to XML translator, 2003. |
Knuth, Donald E., The Art of Computer Programming Second Edition vol. 1 Fundamental Algorithms, 1973. |
Matula, David W., An Algorithm for Subtree Identification, Apr. 1968. |
The Lucene system, which was allegedly used, offered for sale, or sold at least by Nov. 29, 2004, as described by reference to the enclosed documents concerning the structure, function, operation, and/or features of Lucene. |
Sechrest et al., “Blending Hierarchical and Attribute-Based File Naming”, Distributed Computing System, 1992, Proceedings of the 1 ih International Conference on Jun. 9-12, 1992, pp. 572-580. |
Shanmugasundaram et al., “Querying SML Views of Relational Data”, Proceedings of the 2th VLDB Conference, Roma, Italy, 2001, 9 pages. |
Siegel, “All Searches Are Divided into Three Parts String Searches Using Ternary Trees”, ACM, pp. 57-68, 1988. |
Sinha et al., “Efficient Trie Based Sorting of Large Sets of Strings,” ACM, pp. 1-8, 2003. |
Sitaraman, Krishna, Ranganathan, N., and Ejnioui, Abdel, “A VLSI Architecture for Object Recognition using Tree Matching” Proceedings of the IEEE International Conference on Application-Specific Systems, Architectures, and Processors (ASAP'02) Dec. 2001, pp. 1-71. |
Smorynski, Craig, “Logical Number Theory I: An Introduction”, Springer—Verlag Berlin Heidelberg, @1991, Arithmetic Encoding, The Cantor Pairing Function, pp. 14-23, and 305. |
Somani et al., “Phased-Mission System Analysis Using Boolean Algebraic Methods”, May 1994, ACM Press, vol. 22, Issue 1. |
Spinells “Declarative Peephole Optimization Using String Pattern Matching”, ACM, pp. 47-51, 1999. |
Sproat et al., “Compilation of Weighted Finite-State Tranducers from Decision Trees” ACM, pp. 215-222, 1996. |
Stanat, D.F., and McAllister, D.F., “Discrete Mathematics in Computer Science”, Prentice-Hall, 1977, Binary Relations, Ch. 3, Sec. 3.2, Trees, p. 131-145. |
Stefanov “Algorithmic Transformation Techniques for Efficient Exploration of Alternative Application Instances” Journal for the Association for Computing Machinery (ACM) (2002) pp. 7-12, 6 pages, Doc 2234. |
Talukdar, “Learning to Create Data-Integrating Queries”, ACM PVLDB, pp. 785-796, 2008. |
Thiemann, “Grammar-Based Analysis of String Expressions”, ACM, pp. 59-70, 2005. |
Valiente, “Algorithms on Trees and Graphs”, Tree Isomorphism, pp. 151-251, Springer 2002. |
Valiente, Gabriel, “Tree Isomorphism,” of Algorithms on Trees and Graphs, Chapter 4, published by Springer, 2002, 51 pages. |
Vion-Dury, “Experimenting with the Circus Language for XML Modeling and Transformation”, ACM pp. 82-87 (2002), Doc 2352. |
Wagner et al., “The String-to-String Correction Problem”, Journal of the Association for Computing Machinery, vol. 21, No. 1, pp. 168-173, 1974. |
Wu, “A Prime No. Labeling Scheme for Dynamic Ordered XML Trees”, IEEE, 2004, 13 pages. |
Xie et al., “S-Looper: Automatice Summarization for Multipath String Loops”, ACM, pp. 188-198, 2015. |
Yang, “Interactive Hierarchical Dimension Ordering, Spacing and Filtering for Exploration of High Dimensional Datasets”, IEEE, pp. 1-8 (Year: 2013), 8 pages, Doc 2324. |
Yates et al., “A New Approach to Text Searchin”, Communications of the ACM, vol. 35, No. 10, pp. 7 4-82, 1992. |
Zaks, S., “Lexicographic Generation of Ordered Trees”, Dept. of Computer Science, University of Illinois, The Journal of Theoretical Computer Science, vol. 10(1 ), pp. 63-82, Revised 1978. |
Zanibbi, “Recognizing Mathematical Expressions Using Tree Transformation,” IEEE, pp. 1455-1467 (2002), Doc 2353. |
Zhang, B ed-Tree: An All-Purpose Index Structure for String Similarity Search. |
“Core Technology Benchmarks A White Paper”, Jul. 2002, downloaded from the internet Mar. 2, 2004. |
“Origin Data, Inc. White Paper”, @1999, pp. 1-13. |
“The Associative Model of Data White Paper”, Lazy Software, Ltd., 2000. |
ACM Portal Search Results (Kleene and prime and enumeration and operation and natural and numerals and sequences and enumeration and operation) conducted by Examiner on Jul. 18, 2009, 1 page. |
ACM Portal Search Results (Kleene and prime and enumeration and operationand natural and numerals and sequences and “enumeration operation”) conducted by Examiner on Jul. 18, 2009, 6 pages. |
Alderson et al., “Toward an Optimization Driven Framework for Designing and Generating Realistic Internet Topologies” ACM SIGCOMM Computer Communications Review 41, vol. 33, No. 1, pp. 41-46, 2003. |
Apostol, “A Centennial History of the Prime No. Theorem”, Engineering and Science, No. 4, 1996. |
Benedikt et al., “Definable Relations and First-Order Query Languages over Strings” Journal of the ACM, vol. 50, No. 5, pp. 694-751, 2003. |
Boppana et al., “Full Fault Dictionary Storage Based on Labeled Tree Encoding”, Proceedings of 14th VLSI Test Symposium, 1996, pp. 17 4-179. |
Borodin et al., “A Tradeoff Between Search and Update Time for the Implicit Dictionary Problem”, Theoretical Computer Science vol. 1 No. 4 (1990), 425-447. |
Cano et al., “Lazy Evaluation in Penniless Propagation over Join Trees”, Networks, vol. 39(4), 2002 Wiley Periodicals, Inc., 175-185, 2002. |
Caviness et al., “Simplification of Radical Expressions”, ACM, pp. 329-338, 1976. |
Coenen, Frans; Leng, Paul and Ahmed, Shakil; “T-Trees, Vertical Partitioning and Distributed Association Rule Mining”, IEEE, 2003. |
Cole, Richard, Hariharan, Ramesh, and Indyk, Piotr. “Tree pattern matching and subset matching in deterministic O(n log 3 n)-time”, Proceedings of the Tenth Annual ACM-SIAM Symposium on Discrete Algorithms, p. 1-10, Jan. 2, 1999, Baltimore, Maryland, United States. |
Cooper et al., “Oh! Pascal!”, 1982, W.W. Norton & Company, Inc., Chapter 12, Arrays for Random Access, pp. 295-327. |
Dubiner, M., Galil, Z., and Magen, E. “Faster Tree Pattern Matching.”, Journal of the Association for Computing Machinery, vol. 41, No. 2, Mar. 1994, pp. 205-213. |
Durango Bill's Enumeration of Trees. http://web.archive.org/web/20021028184112/http://www.durangobill.com/Trees. html, 1998. |
Er, M.C., “Enumerating Ordered Trees Lexicographically”, The Computation Journal, vol. 28, Issue 5, pp. 538-542, 1985. |
Ferragina et al., “The String B-Tree: A New Data Structure for String Search in External Memory and Its Applications”, Journal of the ACM, vol. 46, No. 2, pp. 236-280, 1999. |
Fluri, “Change Distilling: Tree Differencing for Fine-Grained Source Code Change Extraction”, IEEE pp. 725-743 (2007), Doc 2354. |
Google Search (Kleene prime enumeration operation natural numerals sequences “enumeration operation”) conducted by Examiner on Jul. 18, 2009, 2 pages. |
Google search (Kleene prime enumeration operation natural numerals sequences “Kleene prime”) conducted by Examiner on Jul. 18, 2009, 2 pages. |
Google Search (Kleene prime enumeration operation) conducted by Examiner on Jul. 18, 2009, 2 pages. |
Hirschberg, “Algorithm for Computing Maximal Common Sebsequences”, Communication of the ACM, vol. 18, No. 6, pp. 341-343, 1975. |
Hoffman et al., “Pattern Matching in Trees”, Purdue University, Jan. 1982, Journal for the Association for Computing Machinery, vol. 29, Issue 1 , pp. 68-95. |
Iacob et al., “XPath Extension for Querying Concurrent XML Markup”, Technical Report #TR 394-04, Department of Computer Science, University of Kentucky, Lexington, KY 40506, Mar. 6, 2004, 15 pages. |
IEEE Explore Digital Library Search Result conducted by Examiner on Jul. 18, 2009, 1 page. |
Jaiswal, “Local Pattern Transformation Based Feature Extraction Techniques for Classification of Epileptic EEG Signals”, Biomedical Signal Processing and Control (2017) pp. 81-92, 12 pages, Doc 2205. |
Johnston et al. Advances in Dataflow Programming Languages, ACM Computing Surveys, vol. 36, No. 1, pp. 1-34, 2004. |
Katajainen et al., “Tree Compression and Optimization with Applications”, International Journal of Foundations of Computer Science, vol. 1 No. 4 (1990), 425-447. |
Kharbutli et al., “Using Prime Nos. for Cache Indexing to Eliminate Conflict Misses”, Dept. of Electrical and Computer Engineering, North Carolina State University, Feb. 2004, 24 pages. |
Kilpelainen, “Tree Matching Problems with Applications to Structured Text Databases”, Ph.D. Dissertation, Department of Computer Science, University of Helsinki, Report A-1992-6, Helsinki, Finland, pp. 1-109, Nov. 1992. |
Knott—“A Balanced Tree Storage and Retrieval Algorithm” ACM pp. 175-196, 1971, Doc 2296. |
Knuth, “The Art of Computer Programming”, vol. 1 Fundamental Algorithms, Second edition, Addison-Wesley Series in Computer Science and Information Processing, ISBN 0-201-03809-9, Reading, Massachusetts, Copyright 1973. |
Leinonen et al., “Automation of Document Structure Transformations”, Auditorium, Microteknia Building, University of Kuopio, Nov. 5, 2004, 68 pages. |
Lerman et al., “Learning the Common Structure of Data”, American Association for Artificial Intelligence, AAAI-00 Proceedings, www.aaai.org, Apr. 13, 2000, 6 pages. |
Letourneau, “The Elementary Theory of Object Oriented Arithmetic”, pp. 1-9, Apr. 1990. |
Li—“An Immediate Approach to Balancing Nodes in Binary Search Trees” ACM, pp. 238-245, 2006, Doc 2242. |
Malhotra et al., “A Methodology for Formal Expression of Hierarchy in Model Solution”, IEEE, pp. 258-267, 1983. |
Minn, “Linear Transformation of Multi-Level Signal Set in Multi-Code Cdma”, IEEE (2001) pp. 1239-1243, 5 pages, Doc 2214. |
Murray, “Code Transformation and Instruction Set Extension”, Journal of the Association for Computing Machinery (2009) pp. 1-31, 32 pages, Doc 2215. |
Navarro, “A Guided Tour to Approximate String Matching”, ACM Computing Surveys, vol. 33, No. 1, pp. 31-88, 2001. |
Neven, Frank and Thomas Schwentick, “Expressive and efficient pattern languages for tree-structured data” Proceedings of the Nineteenth Acm Sigact-Sigmod-Sigart Symposium on Principles of Database Systems, May 2000. |
Paik, “Mining Association Rules in Tree Structured XML Data” ACM, pp. 807-811, 2009, 5 pages, Doc 2243. |
Prasad et al., “Efficient Bit-Parallel Multi-Patterns String Matching Algorithms for Limited Expression”, ACM, pp. 1-6, 2010. |
Ramesh, R. and Ramakrishnan, I.V., “Nonlinear Pattern Matching in Trees.” Journal of the Association for Computer Machinery, vol. 39, No. 2. Apr. 1992, pp. 295-316. |
Reiss, “Semantics-Based Code Search”, IEEE ICSE, pp. 243-253, 2009. |
Rizum, “Code Transformation by Direct Transformation of ASTs”, Journal of the Association for Computing Machinery (2015) pp. 1-7, 7 pages, Doc 2220. |
Sahinalp, “Distance Based Indexing for String Proximity Search”, IEEE, pp. 125-136 (2003), Doc 2355. |
Schmidt et al., “Comparision of Tree and Graph Encodings as Function of Problem Complexity”, ACM, pp. 1674-1679, 2007. |
Number | Date | Country | |
---|---|---|---|
20230229647 A1 | Jul 2023 | US |
Number | Date | Country | |
---|---|---|---|
60640427 | Dec 2004 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 17590229 | Feb 2022 | US |
Child | 18182425 | US | |
Parent | 15464205 | Mar 2017 | US |
Child | 17590229 | US | |
Parent | 15081612 | Mar 2016 | US |
Child | 15464205 | US | |
Parent | 13632581 | Oct 2012 | US |
Child | 15081612 | US | |
Parent | 11319758 | Dec 2005 | US |
Child | 13632581 | US |