This invention relates to electronic commerce and more particularly to translation between product classification schemas.
Due to the ever-increasing popularity and accessibility of the Internet as a medium of communication, the number of business transactions conducted using the Internet is also increasing, as are the numbers of buyers and sellers participating in electronic marketplaces providing a forum for these transactions. The majority of electronic commerce (“e-commerce”) transactions occur when a buyer determines a need for a product, identifies a seller that provides that product, and accesses the seller's web site to arrange a purchase of the product. If the buyer does not have a preferred seller or if the buyer is purchasing the product for the first time, the buyer will often perform a search for a number of sellers that offer the product and then access numerous seller web sites to determine which seller offers certain desired product features at the best price and under the best terms for the buyer. The matching phase of e-commerce transactions (matching the buyer with a particular seller) is often inefficient because of the large amount of searching involved in finding a product and because once a particular product is found, the various offerings of that product by different sellers may not be easily compared.
According to the present invention, disadvantages and problems associated with previous e-commerce techniques have been substantially reduced or eliminated.
In one embodiment of the present invention, a schema translation tool includes a mapping module that receives information regarding a source schema and a target schema. The source and target schemas each include a taxonomy that includes a hierarchy of classes into which products may be categorized. At least the source schema further includes a product ontology, including one or more product attributes, that is associated with one or more of the classes. The mapping module associates one or more source classes of the source schema with one or more target classes of the target schema. The schema translation tool further includes an ontology generation module that generates a product ontology for each of the target classes based on the product ontologies of the associated source classes.
Particular embodiments of the present invention may provide one or more technical advantages. For example, certain embodiments of the present invention may be used in association with a global content directory that categorizes a number of different products and provides a portal through which a buyer may search for particular products and establish communications with an appropriate seller of a desired product. The global content directory may use one or more schema to categorize the various products. These schema include a taxonomy, which is a hierarchy of classes into which the products may be categorized. However, a buyer or other user of the global content directory may prefer that the products be categorized according to a taxonomy not provided by the global content directory.
Therefore, certain embodiments of the present invention provide a translation tool that translates a source schema having one taxonomy to a target schema having a different taxonomy. Furthermore, one or more of the classes included in either of the taxonomies may have an associated ontology, which includes one or more attributes associated with a product or a seller of a product. The translation tool provided by particular embodiments may also translate the ontology of classes in the source schema to associated classes in the target schemas. Therefore, although the global content directory may initially provide only a limited number of schemas in which products are categorized, embodiments of the present invention may be used to translate these schemas to different schemas desired by particular buyers. Such a translation provides such buyers with a more effective and efficient product transaction process and attracts a larger number of variety of buyers to the global content directory.
Other technical advantages may be readily apparent to those skilled in the art from the following figures, description, and claims.
To provide a more complete understanding of the present invention and the features and advantages thereof, reference is made to the following description taken in conjunction with the accompanying drawings, in which:
Although buyers 20 and sellers 30 are described as separate entities, a buyer 20 in one transaction may be a seller 30 in another transaction, and vice versa. Moreover, reference to “buyer” or “seller” is meant to include a person, a computer system, an organization, or another entity where appropriate. For example, a buyer 20 may include a computer programmed to autonomously identify a need for a product, search for that product, and buy that product upon identifying a suitable seller. Although buying and selling are primarily described herein, the present invention contemplates any appropriate e-commerce transaction. Moreover, reference to “products” is meant to include goods, real property, services, information, or any other suitable tangible or intangible things.
A typical e-commerce transaction may involve a “matching” phase and a “transactional” phase. During the matching phase, a buyer 20 may search for a suitable product (meaning any good, real property, service, information, or other tangible or intangible thing that may be the subject of an e-commerce transaction) offered by one or more sellers 30, identify the most suitable seller 30 (which may involve, for example, identifying the seller 30 offering the lowest price), and contact that seller 30 to enter the transactional phase. During the transactional phase, the buyer 20 and seller 30 may negotiate a contract for the sale of the product (which may involve, for example, more clearly defining the subject of the transaction, negotiating a price, and reaching an agreement on supply logistics) and generate a legal document embodying the terms of the negotiated contract. To identify the most suitable seller 30 during the matching phase without the use of GCD 42, a buyer 20 may have to access numerous seller web sites to determine which seller 30 offers certain desired features of the product at the best price. Sellers 30 may each provide one or more databases 32, such as relational databases, that include data identifying the products available from sellers 30 and their features. Each database 32 may be accessed through the associated seller's web site or in any other appropriate manner. The multiple one-to-one (one buyer 20 to one seller 30) searches that this process requires are inefficient and expensive because of the large amount of searching involved in finding a product and because the various offerings of that product by different sellers 30 may not be easily compared.
Alternatively, multiple sellers 30 may be grouped in an electronic marketplace according to the products they provide and a buyer 20 may search the offerings of the multiple sellers 30 at a single web site. However, if buyer 20 wishes to obtain several different types of products, buyer 20 may have to go to several different types of marketplaces. Furthermore, there may be numerous competing marketplaces that buyer 20 has to search to perform the matching phase of a transaction for a particular product. One potential method of addressing this problem is to create a global product database that potentially includes data identifying the features of all the products that any buyer may wish to obtain. Therefore, the global database would include the combined contents of every database 32 associated with every seller 30. However, such a global database would have many problems. For example, the sheer size of the database would make it difficult to search and thus the database would suffer from performance problems. In addition, it would be difficult to allow large numbers of buyers 20 to search the database at once. Furthermore, all sellers 30 would be required to access the global database to update their information and the entire database would have to be updated each time a change is made. Many other problems might also exist.
A solution to the above problems, at least in part, is GCD 42. GCD 42 is a universal directory of the contents of multiple seller databases 32 (and potentially all seller databases 32). GCD 42 may be implemented using one or more servers 40 or other computers located at one or more locations. Most or all of the content in these seller databases 32 remains stored in databases 32, but this content is accessible using GCD 42. Therefore, like the global database described above, GCD 42 provides buyers 20 with access to product data relating to a multitude of products (and potentially seller data relating to one or more sellers 30 of the products), but unlike the global database, GCD 42 does not attempt to store all of this data in one enormous database. Where appropriate, reference to “data” is meant to include product data (meaning information reflecting values for certain attributes of a product), seller data (meaning information reflecting values for certain seller attributes), or both product data and seller data.
GCD 42 provides a directory of products using a directory structure in which products are organized using a hierarchical classification system. A buyer 20 may navigate or search the directory to find a particular product class into which products are categorized. The product data (and potentially seller data) associated with a product included in a product class may actually be stored in and obtained by GCD 42 from a seller database 32. However, the requested data may be transparently provided to buyer 20 such that all of the product data may appear to buyer 20 as being included in GCD 42. Although product and/or seller data has primarily been described as being stored in seller databases 32, the present invention contemplates product data being stored in any suitable manner and being retrieved from any suitable sources. For example, system 10 may include a shared data repository 34 that contains product data and/or seller data that may be combined with data from one or more seller databases 32, as described in further detail below. Furthermore, as is described in further detail below with reference to
In addition to a taxonomy and product ontologies, a schema may include a set of attributes for each seller (which may be referred to as a “seller ontology”). Such attributes may include geographic restrictions (such as served markets), currencies accepted by each seller, collaboration tools accepted by each seller, contract terms accepted by each seller, types of contracts accepted by each seller, levels of buyer credit required by each seller, and any other suitable seller attributes. Similar to a products within a product class, sellers offering products within a product class may be defined by seller attribute values corresponding to seller attributes. Accordingly, a schema may include a set of classes, each including one or more products, and each class may be associated with a set of product attributes and a set of seller attributes.
In example directory structure 44, products may be organized and cataloged according to industry standard schemas 46 or other appropriate schemas, as described below. Within industry standard schemas 46, there are two example classes: a direct materials class 48 and an indirect materials class 50. Each of these classes 48 and 50 includes several sub-classes (which may themselves include sub-classes). Therefore, the numerous classes of directory structure 44 form a “tree-like” hierarchical structure into which products may be categorized. For example purposes, certain portions of directory structure 44 are “expanded” in
A buyer 20 may navigate through directory structure 44 by expanding or collapsing various classes as desired. For example,
Buyer 20 may also search for sellers matching one or more seller attribute values within a product class. For example, in addition to searching for all products in writing utensils class 56 that are blue felt-tip pins having medium tips, buyer 20 may search for sellers 30 serving Texas that accept U.S. dollars. Buyer 20 may search for products matching certain product attribute values and sellers matching certain seller attribute values in any appropriate manner. In one embodiment, for example, buyer 20 provides search criteria including both values for product attributes and for seller attributes (search criteria may instead be generated automatically, in whole or in part, as described below), and server 40 searches for products that match the product attribute criteria and are offered by sellers matching the seller attribute criteria. In another embodiment, buyer 20 provides only product attribute values as search criteria, and server 40 limits its search for products matching the product attribute criteria to databases 32 associated with sellers 30 known to match seller attribute criteria that buyer 20 may want according to a buyer profile or otherwise.
As described above, in one embodiment product data (at least product data more detailed than data provided by a taxonomy) and seller data are not stored in GCD 42, but are stored in databases 32. For example, a seller 30 may maintain a relational database 32 that includes a plurality of tables containing product attribute values for a variety of products and seller attribute values for each product, a set of products, or all of the products offered by seller 30. Product data and seller data may be integrated into one or more tables or may be segregated into different tables. Moreover, product data and seller data for a seller 30 may be stored in the same or separate databases. One or more pointers may be associated with each class to identify the location of one or more databases 32 that include product data and/or seller data for products contained in that class or to identify particular data in databases 32. Therefore, GCD 42 may execute a search for products in databases 32 identified by a pointer corresponding to a user-selected (or automatically selected) class. GCD 42 may also return the network location (such as a uniform resource locator (URL) or other network address) of the database 32 to buyer 20 so that buyer 20 may independently access database 32. Databases 32 may be searched using any appropriate method including, but not limited to, a structured query language (SQL) query.
GCD 42 may be implemented using the lightweight directory access protocol (LDAP), which enables directories to be provided using the tree-like structure described above. However, any other appropriate technique or protocol for creating GCD 42 may alternatively be used and GCD 42 may have any appropriate structure. Furthermore, GCD 42 may be an object-oriented directory (which is also provided by LDAP) such that each class in directory structure 44 includes the attributes of parent classes in which the class is a sub-class. In this embodiment, a product class listed at the end of a branch of the tree structure (a leaf class) includes all of the attributes of its parent classes in the branch. Furthermore, each product included in a database 32 may be an object that includes all the attributes of the classes in which the product is included. Thus, when a search is performed from a leaf class of directory structure 44, the search query may automatically include any appropriate attributes of parent classes of the leaf class.
For example, if a buyer 20 has navigated through directory structure 44 to felt-tip pens class 60b, a search performed by buyer 20 (or by GCD 42 on behalf of buyer 20) from felt-tip pens class 60b may automatically be limited to a search for felt-tip pens and buyer 20 may introduce additional desired search criteria (such as blue ink and medium tip). Therefore, if a database 32 searched includes product data relating to a variety of writing utensils, a search of database 32 may be automatically limited by GCD 42 to only include felt-tip pens within that database 32. Buyer 20 may also identify additional product attribute values and/or seller attribute values as additional search criteria.
Table 150 also includes a number of rows 154 that may each correspond to a particular product and that each include values for one or more of the product attributes and seller attributes. Each of the values (which may be numeric, textual, or in any other appropriate format) is located at the intersection of the row 154 associated with a particular product and the column 152 that includes a particular product attribute or seller attribute. Each of these intersections may be referred to as a field or cell 156 of table 150. Where seller data and product data are integrated, each row 154 may contain all of the product data and seller data for the product corresponding to that row 154. Alternatively, there may be a row or set of rows dedicated to seller data that may apply to all products offered by a seller 30 or a subset of all such products. Where seller data and product data are segregated, each row in the seller data table may correspond to a set of seller attribute values that may be linked to a set of one or more products in the product data table such that seller data for a product may be accessed when product data for that product is accessed, and vice versa.
The data in one or more columns 152 of table 150 may be indexed to increase the speed with which database reads may be conducted. For example, the fields 156 of ink color column 152d and tip size column 152e may be indexed so that a database query for a pen having a particular ink color and tip size may be quickly performed. Data in table 150 may be indexed using any appropriate database indexing technique. The typical result of such indexing is that when GCD 42 or a buyer 20 requests indexed data from a database 32 and/or repository 34, the associated database management system (or other appropriate interface to database 32 and/or repository 34) does not have to search through every field 156 in the tables 150 included in database 32 and/or repository 34 to locate the requested data. Instead, the data may be indexed such that when a query is submitted for products having certain product attribute values and/or sellers 30 having certain seller attribute values that have been indexed, the database management system already knows the locations of such products in table 150 and may return data associated with these products without searching the entire table 150 or database 32 and/or repository 34 for the products. For example, if the ink color fields 156 and tip size fields 156 of columns 152d and 152e, respectively, are indexed, the index will typically identify the location of all products having black ink and a medium tip size.
If a query is submitted that also specifies a value of one or more non-indexed product attributes (for example, a query for pens manufactured by ABC Company, if the manufacturer fields 156 in column 152c are not indexed) and/or seller attributes, then the associated database management system may perform a search of database 32 and/or repository 34 for products that include the specified value of the one or more non-indexed attributes or seller attributes. However, such a search may be limited to the products already identified (using the index) as including specified values of indexed attributes (for example, pens having black ink and a medium tip) and/or seller attributes that are also included in the search. Therefore, the amount of time required to perform the search may be reduced even though one or more of the product attribute values or seller attribute values that are searched for are not indexed.
Returning to
In summary, a buyer 20 may search for a product matching certain product attribute values available from a seller matching certain seller attribute values using GCD 42 and thus eliminate or reduce the need for buyer 20 to individually search numerous seller databases 32 to find the desired product available from a suitable seller. GCD 42 provides access to product and/or seller data relating to these numerous products using directory structure 44, which organizes products using a hierarchical, object-oriented classification system. Buyer 20 may navigate or search directory structure 44 to find a particular classification of products and various information associated with the products within this classification, initiate a search of databases 32 including product and/or seller data relating to a product, and then communicate with an appropriate database 32 through GCD server 40 or otherwise. Such access to vast numbers of products is provided without the requirement that all data about the products and/or sellers be stored in a global database. Instead, this data may be stored in seller databases 32 that can be readily accessed using GCD 42.
Although example directory structure 44 may use industry standard schemas 46 as described above with reference to
Furthermore, although GCD 42 may not provide an alternative schema desired by a particular user, a schema 46 or 62 provided by GCD 42 may be translated to the alternative schema desired by the user. As described above, the schema 46 or 62 provided by GCD 42 include “rich” content in that these schemas 46 or 62 include both a taxonomy (hierarchy of product classes) and an ontology (product and/or seller attributes associated with each class). However, many commonly used schema, such as the United Nations Standard Products and Services Classification (UNSPSC) schema, include a taxonomy but do not include an ontology. Therefore, to translate a GCD schema 46 or 62 to such an “ontology-less” schema, the taxonomy of the GCD schema 46 or 62 is mapped to the taxonomy of the ontology-less schema and an ontology is created for each class in the ontology-less schema.
After the leaf classes 72 of schema 70 have been mapped to classes 82 of schema 80, an ontology may be generated for classes 82 based on the ontology of the leaf classes 72 mapped to classes 82. This ontology creation process may be performed automatically by ontology generation module 38 of translation tool 36. As with mapping module 37, ontology generation module 38 may be implemented as any appropriate combination of software and/or hardware associated with GCD server 40 or with any other appropriate component of system 10. Furthermore, mapping module 37 and ontology generation module 38 may be associated with and executed by the same or by different computers. Ontology generation module 38 creates an ontology for a class 82 by determining the ontology of each leaf class 72 that was mapped to the class 82. The ontology for class 82 is then defined as the intersection of the ontologies of the classes 72 that were mapped to class 82. If a single class 72 was mapped to class 82, the ontology of class 82 may be the ontology of the single class 72. As an example, referring to
As described above, the product ontology of a particular class 72 includes the product attributes associated with the class 72 plus the product attributes associated with each of the parent classes 72 of the class 72 (the product attributes associated with each class are indicated in brackets next to the class name in
The product attributes that are not included in the intersection of the ontologies of the classes 72 mapped to a particular class 82 (“temp” and “gas” in the above example) may be used to create subclasses 82 of the particular class (and the pointers associated with the corresponding class 72 may be associated with each subclass 82) or the product attributes may not be included in the ontology of any class 82. Alternatively, the ontology of a particular class 82 may be created from the union of the ontologies of the classes 72 mapped to the class 82. However, in such a case, not all of the products associated with the class 82 (which were associated with the corresponding classes 72) will have associated values for each of the product attributes. Furthermore, any other appropriate technique may be used to create an ontology for a class 82 from the ontologies of classes 72.
After ontologies have been generated for the classes 82 to which classes 72 were associated, there may be classes 82 having the same parent class 82 that have common product attributes in their ontologies. For example, “Batteries” class 82 may have a generated ontology of <voltage, application, type, size>and the other classes 82 included in “Electrical Parts” class 82 may also have generated ontologies. The ontology for “Electrical Parts” class 82 may be formed from the intersection of these ontologies. For example, if all the ontologies of the classes 82 included in “Electrical Parts” class 82 include “voltage” and “application” as attributes, then these two attributes may form the ontology for “Electrical Parts” class 82. These two attributes may then be removed from the attributes associated with the classes 82 under the “Electrical Parts” class 82 since these classes 82 by definition include the attributes of “Electrical Parts” class 82 in their ontologies.
This process may be repeated for each class 82 of schema 80. For example, an ontology may be created for “Marine” class 82 from the intersection (if any) of the ontologies associated with the classes 82 included in “Marine” class 82 (such as “Electrical Parts” class 82). Therefore, in summary, each leaf class 72 of schema 70 is mapped to the most appropriate class or classes 82 of schema 80 and an ontology is created for these classes 82 from the associated mapped classes 72. Then based on the relationship between classes 82 for which an ontology has been generated and the other classes 82 in schema 80, ontologies may also be generated for these other classes 82, as described above, until all appropriate classes 82 have an associated ontology mapped from the ontology of classes 72 of schema 70.
Mapping module 37 receives instructions at step 164 from the user regarding the mapping of classes from the source schema to the target schema. For example, mapping module 37 may receive a series of communications from a user in response to the user “dragging and dropping” one or more classes from the source schema (“source classes”) to one or more classes of the target schema (“target classes”). Any other appropriate instructions from the user regarding the mapping of classes may also be used. At step 165, mapping module associates one or more of the source classes with one or more of the target classes according to the mapping instructions received from the user. At step 166, mapping module 37 (or ontology generation module 38) associates the ontology of each source class with its associated target class or classes. Mapping module 37 also associates the pointers associated with each source class to the associated target class at step 168. Therefore, if a buyer 20 selects a particular target class and performs a search for products categorized in that class, the seller databases 32 and/or repository 34 including product data for these products will be searched.
At step 170, ontology generation module 38 generates an ontology for the target classes from the intersection of the ontologies of the source classes associated with each target class, as described above. Ontology generation module 38 may receive any required information regarding the mappings and the ontologies from mapping module 37 or data storage associated with translation tool 36. Ontology generation module 38 also generates, at step 172, an ontology for the parent classes of the target classes from the intersection of the ontologies of the child classes of each parent class, as described above. At step 174, ontology generation module 38 generates ontologies for the parent classes of the classes for which ontologies were created at step 172 (from the intersection of the child class ontologies) and also for all appropriate classes above these classes in the hierarchy of the taxonomy until an ontology has been so generated for all appropriate classes in the target schema, at which point the method ends.
In an example transaction, a buyer 20 may access a GCD interface 43 and perform a search of GCD 42. GCD interface 43 may allow buyer 20 to both navigate or “browse” the classes of GCD 42 and to search for a particular class or classes. For example, buyer 20 may either navigate GCD 42 to find a class into which pens are categorized or buyer 20 may search GCD 42 for class names including the word “pen.” Any other suitable methods for identifying a particular class may also be used. Furthermore, as described above, if GCD 42 does not provide a taxonomy of product classes that is desired by the user, the user may initiate the translation of an existing schema into a desired schema using translation tool 36, which may be integral with or separate from GCD server 40. Buyer 20 may access translation tool 36 directly (using network 12), using GCD interface 43, or using any other appropriate technique. When buyer 20 has found a suitable schema and located the appropriate class for the product buyer 20 desires, buyer 20 may then request a listing of products in that class matching certain product attribute values. For example, if buyer 20 is browsing felt-tip pens class 60b, buyer 20 may request all products in class 60b (felt-tip pens) that have red ink and a fine tip and that are sold by a seller 30 located in the United States.
A search interface 45, or any other appropriate component of GCD server 40, may facilitate such a request by searching or requesting searches of repository 34 and/or seller databases 32 identified by one or more pointers associated with felt-tip pens class 60b, as described above. Search interface 45 may provide buyer 20 a search form in which to enter one or more search criteria. The types of search criteria that may be used may be identified in the search form or buyer may be allowed to perform a general search of databases 32 and/or repository 34 for certain terms. For example, search interface 45 may provide buyer 20 with a search form tailored for class 60b that includes fields where buyer 20 can specify a desired ink color, tip thickness, or any other appropriate product-related or seller-related criteria. In one embodiment, the fields of the search form correspond to some or all of the product attributes within the product ontology and/or seller attributes within the seller ontology corresponding to the product class that has been selected, and buyer 20 may enter values for the product attributes and seller attributes in the corresponding search form fields. In lieu of a search form, search interface 45 may instead provide a single field where buyer can enter in desired search terms, such as “red” and “fine” (multiple search terms may be entered using Boolean operators or any other appropriate technique).
Search interface 45, or any other appropriate component of GCD server 40, may also facilitate search requests by accessing a buyer profile for buyer 20 containing information compiled from previous search requests made by buyer 20, previous e-commerce transactions involving buyer 20, or other events or actions on the part of buyer 20. For example, a buyer profile may contain a list of sellers 30 matching seller attribute values that buyer 20 may want. Such a list may be compiled from the results of previous searches by buyer 20. Search interface 45 may access the profile for buyer 20 for any suitable purpose. In one embodiment, search interface 45 may access the profile for buyer 20 to automatically generate search criteria, such as product attribute values and/or seller attribute values, for a search. Search interface 45 may also access the profile for buyer 20 to limit its search for products matching product attribute values provided by buyer 20 (or generated automatically) to databases 32 associated with sellers 30 known to match seller attribute values that buyer 20 may want (and/or data in repository 34 associated with such sellers 30). Based on search criteria provided by buyer 20 or automatically generated, search interface 45 may communicate a query to the appropriate seller database(s) 32 and/or repository 34 requesting that databases 32 and/or repository 34 each return a listing of all products (including associated product data and/or seller data) that meet the search criteria. Databases 32 and/or repository 34 may also return data relating to attribute values that were not included in the search criteria. For example, databases 32 may return a price and availability of products that meet the search criteria even if price and availability were not search criteria. The responses to the queries of databases 32 and/or repository 34 may be displayed to buyer 20 in any appropriate manner. For example, the products may be listed in order of relevance to the search criteria according to any suitable matching criteria. Furthermore, GCD 42 may reorder the product listing based on a request from buyer 20. For example, buyer 20 may request that the matching products be listed in order from least expensive to most expensive. Alternatively, the search results may be communicated directly to buyer 20 from databases 32 and/or repository 34.
Buyer 20 may select a product from the product listing to indicate a desire to initiate a transaction regarding the product, such as a purchase of the product. On such a selection, GCD 42 may communicate a repository identifier (RID) identifying the selected seller 30 and a globally unique identifier (GUID) for the product to buyer 20. For example, an RID may be the network address (such as an IP address) of a seller network node 30 or may be associated with the network address in a table (in which case GCD 42 may use the RID to look up the associated network address and then communicate the network address to buyer 20). Buyer may access the seller 30 using the RID (or network address) and request a transaction regarding the product using the GUID. GCD 42 may even provide a link including a URL of a web site associated with the seller 30 or may provide another appropriate method for buyer 20 to be connected to seller 20. Although only a single example arrow (between buyer 20n and seller 30n) is shown to illustrate communication between buyers 20 and sellers 30, it should be understood that any buyer 20 may communicate with any seller 30 to conduct appropriate transactions.
Although the present invention has been described with several embodiments, divers changes, substitutions, variations, alterations, and modifications may be suggested to one skilled in the art, and it is intended that the invention encompass all such changes, substitutions, variations, alterations, and modifications falling within the spirit and scope of the appended claims.
Number | Name | Date | Kind |
---|---|---|---|
3961164 | Reed et al. | Jun 1976 | A |
5347632 | Filepp et al. | Sep 1994 | A |
5564043 | Siefert | Oct 1996 | A |
5642419 | Rosen | Jun 1997 | A |
5694546 | Reisman | Dec 1997 | A |
5721832 | Westrope et al. | Feb 1998 | A |
5727129 | Barrett et al. | Mar 1998 | A |
5790677 | Fox et al. | Aug 1998 | A |
5870473 | Boesch et al. | Feb 1999 | A |
5918229 | Davis et al. | Jun 1999 | A |
5926797 | Goodwin, III | Jul 1999 | A |
5935207 | Logue et al. | Aug 1999 | A |
5963134 | Bowers et al. | Oct 1999 | A |
5970471 | Hill | Oct 1999 | A |
5970490 | Morgenstern | Oct 1999 | A |
5987233 | Humphrey | Nov 1999 | A |
6006218 | Breese et al. | Dec 1999 | A |
6038668 | Chipman et al. | Mar 2000 | A |
6049673 | McComb et al. | Apr 2000 | A |
6078891 | Riordan et al. | Jun 2000 | A |
6081840 | Zhao | Jun 2000 | A |
6094680 | Hokanson | Jul 2000 | A |
6101515 | Wical et al. | Aug 2000 | A |
6105134 | Pinder et al. | Aug 2000 | A |
6128600 | Imamura et al. | Oct 2000 | A |
6128624 | Papierniak et al. | Oct 2000 | A |
6144996 | Starnes et al. | Nov 2000 | A |
6154738 | Call | Nov 2000 | A |
6189043 | Buyukkoc et al. | Feb 2001 | B1 |
6192131 | Geer, Jr. et al. | Feb 2001 | B1 |
6199082 | Ferrel et al. | Mar 2001 | B1 |
6212512 | Barney et al. | Apr 2001 | B1 |
6236975 | Boe et al. | May 2001 | B1 |
6236978 | Tuzhilin | May 2001 | B1 |
6271846 | Martinez et al. | Aug 2001 | B1 |
6285366 | Ng et al. | Sep 2001 | B1 |
6286002 | Axaopoulos et al. | Sep 2001 | B1 |
6289382 | Bowman-Amuah | Sep 2001 | B1 |
6324522 | Peterson et al. | Nov 2001 | B2 |
6334131 | Chakrabarti et al. | Dec 2001 | B2 |
6336910 | Ohta et al. | Jan 2002 | B1 |
6341280 | Glass et al. | Jan 2002 | B1 |
6343287 | Kumar et al. | Jan 2002 | B1 |
6356899 | Chakrabarti et al. | Mar 2002 | B1 |
6366910 | Rajaraman et al. | Apr 2002 | B1 |
6370527 | Singhal | Apr 2002 | B1 |
6415320 | Hess et al. | Jul 2002 | B1 |
6418448 | Sarkar | Jul 2002 | B1 |
6460038 | Khan et al. | Oct 2002 | B1 |
6466240 | Maslov | Oct 2002 | B1 |
6466918 | Spiegel et al. | Oct 2002 | B1 |
6476832 | Park | Nov 2002 | B1 |
6489968 | Ortega et al. | Dec 2002 | B1 |
6490567 | Gregory | Dec 2002 | B1 |
6490619 | Byrne et al. | Dec 2002 | B1 |
6516350 | Lumelsky et al. | Feb 2003 | B1 |
6532481 | Fassett, Jr. | Mar 2003 | B1 |
6553364 | Wu | Apr 2003 | B1 |
6581072 | Mathur et al. | Jun 2003 | B1 |
6591252 | Young | Jul 2003 | B1 |
6708161 | Tenorio et al. | Mar 2004 | B2 |
6745177 | Kepler et al. | Jun 2004 | B2 |
6775655 | Peinado et al. | Aug 2004 | B1 |
6778991 | Tenorio | Aug 2004 | B2 |
6823495 | Vedula et al. | Nov 2004 | B1 |
6874141 | Swamy et al. | Mar 2005 | B1 |
6907401 | Vittal et al. | Jun 2005 | B1 |
7010539 | Haas et al. | Mar 2006 | B1 |
7275079 | Brodsky et al. | Sep 2007 | B2 |
7373349 | O'Brien et al. | May 2008 | B2 |
7406436 | Reisman | Jul 2008 | B1 |
7512558 | Elad et al. | Mar 2009 | B1 |
7660874 | Meltzer et al. | Feb 2010 | B1 |
20010016846 | Chakrabarti et al. | Aug 2001 | A1 |
20010025262 | Ahmed | Sep 2001 | A1 |
20010032162 | Alsberg et al. | Oct 2001 | A1 |
20010034814 | Rosenzweig | Oct 2001 | A1 |
20010044751 | Pugliese, III et al. | Nov 2001 | A1 |
20010051927 | London et al. | Dec 2001 | A1 |
20020026386 | Walden | Feb 2002 | A1 |
20020032597 | Chanos | Mar 2002 | A1 |
20020046147 | Livesay et al. | Apr 2002 | A1 |
20020046187 | Vargas et al. | Apr 2002 | A1 |
20020069157 | Jordan | Jun 2002 | A1 |
20020077930 | Trubey et al. | Jun 2002 | A1 |
20020082932 | Chinnappan et al. | Jun 2002 | A1 |
20020083048 | Tenorio et al. | Jun 2002 | A1 |
20020095355 | Walker et al. | Jul 2002 | A1 |
20020099578 | Eicher et al. | Jul 2002 | A1 |
20020099598 | Eicher et al. | Jul 2002 | A1 |
20020111870 | Chinnappan et al. | Aug 2002 | A1 |
20020111922 | Young et al. | Aug 2002 | A1 |
20020120598 | Shadmon et al. | Aug 2002 | A1 |
20020123955 | Andreski et al. | Sep 2002 | A1 |
20020147704 | Borchers | Oct 2002 | A1 |
20030018558 | Heffner et al. | Jan 2003 | A1 |
20030033205 | Nowers et al. | Feb 2003 | A1 |
20030055754 | Sullivan | Mar 2003 | A1 |
20030093320 | Sullivan | May 2003 | A1 |
20030149934 | Worden | Aug 2003 | A1 |
20030167213 | Jammes et al. | Sep 2003 | A1 |
20030195877 | Ford et al. | Oct 2003 | A1 |
20030208507 | Venkatram | Nov 2003 | A1 |
20040015829 | Mullins et al. | Jan 2004 | A1 |
20040068576 | Lindbo et al. | Apr 2004 | A1 |
20040128215 | Florance et al. | Jul 2004 | A1 |
20040181493 | Cross et al. | Sep 2004 | A1 |
20050021513 | Vedula et al. | Jan 2005 | A1 |
20050033733 | Shadmon et al. | Feb 2005 | A1 |
20050125781 | Swamy et al. | Jun 2005 | A1 |
20050234902 | Meredith et al. | Oct 2005 | A1 |
20060156253 | Schreiber et al. | Jul 2006 | A1 |
20070081197 | Omoigui | Apr 2007 | A1 |
20070088757 | Mullins et al. | Apr 2007 | A1 |
20070112843 | Swamy et al. | May 2007 | A1 |
20070226084 | Cowles | Sep 2007 | A1 |
20080126265 | Livesay et al. | May 2008 | A1 |
20080133381 | O'Brien et al. | Jun 2008 | A1 |