Patent Application
20060259510
The present invention generally relates to search queries, and more particularly to search queries that may not formulated as a natural language question.
Accompanying the rapid growth in the amount of information available in the form of documents stored in databases has come an increased need to efficiently extract information relevant to a specific need. Traditional searching methods search and retrieve documents according to the words in a given input query. Search engines allow users to find documents containing one or more words or phrases, often referred to as keywords, found in the input query and return a list of relevant documents for the input query. For instance, with traditional search and retrieval methods, the input query
returns a list of documents containing one or both words Time or Warner. Search engines may also permit the formulation of Boolean queries, which allow words in the query to be combined using logical operations such as AND, OR, and NOT. Such operations allow to specify which words must appear in the documents, which words may appear in the documents, and which words may not appear in the documents. For example, using a traditional Boolean search engine, the query
selects documents that contain the word US and Open but not the word golf
Another feature that may be used when performing queries with traditional search engines is the ability to trigger a search for phrases in documents. For example the query
retrieves documents that contain the exact phrase “US Open” while rejecting documents that contain the word US and/or the word Open separately. Examples of search engines offering these capabilities are search engines used with the World Wide Web such as AltaVista™, Lycos™, Inktomi™, InfoSeek™, NorthernLight™, HotBot™, MSN Search™, Google™ and Yahoo!™. Additional search engines include those used for searching documents found in databases, digital libraries or other information sources such as Inktomi Enterprise Search™, Verity® K2 Enterprise, or AltaVista® Search Software.
The result of a search using search engines such as those mentioned above is a list of relevant documents, generally displayed in some order, for example, from the most relevant document to the least relevant document. To present documents in an order, search engines rank the documents according to some metric. Typically, the ranking will first show documents containing the highest number of keywords.
For example, referring to
One form of output of traditional search engines that may be queried are documents which match words in the input query. Although documents may be what users are seeking when using traditional search engines, it may also be that a user is seeking information other than document names or URLs.
For example, as illustrated in the screen display 20 of
The above-referenced query may be an input query to a traditional search engines which display as query results the documents including words from the input query. It may be the case that the user is looking for the actual names of tennis players who won the US Open.
As another example, as illustrated in the screen display 30 of
In the foregoing description as illustrated in the screen displays 10, 20, 30 and 40, conventional search engines and World Wide Web search engines expect that the user is seeking documents that include particular term or terms of an input query. It may be desirable to provide a search engine, for example, with the ability to return information besides documents and to infer additional information that a user may be seeking based on a particular input query.
For example, when a user issues the query tennis US Open winners, the user may be seeking the names of the tennis players who won the US Open. Traditional search engines are unable to recognize that a user is seeking the names of tennis players and not looking for documents including the terms from the input query. Similarly, the query Oregon senators, may be intended to seek the names of senators of Oregon and not to seek documents. As yet another example used above, when a user issues the query Bruce Willis movies, the user may not be looking for the actual documents including input query terms, but may rather be looking for the titles of movies in which Bruce Willis appears.
Question-answering systems, for example, such as described in pending U.S. patent application Ser. No. 09/845,571, filed Apr. 30, 2001, entitled SYSTEM FOR ANSWERING NATURAL LANGUAGE QUESTIONS, (hereinafter “the Question Answering application”), may be used to provide answers to questions. However, the foregoing systems expect input in the form of a question. For example, a user seeking for the names of senators of Oregon, may issue the question
Although question-answering systems will give the names of senators of Oregon as results, the user is expected to type a question and is unable to issue a short and simple query as senators of Oregon.
The foregoing question-answering systems may suffer from a drawback in that the user is expected to input a question, and may not accept as input short queries which do not form a question. Furthermore, users of traditional search engines and systems may be more inclined to type short keyword queries (e.g., one, two or at most three words) than to enter input queries in the form of questions which may be much longer (e.g., more than five words).
It may also be desirable to have a system and method for inferring additional information from a query and provide as output answers in response to the inferred additional information. It may also be desirable to provide the document lists produced in accordance with the original input query terms. It may also be desirable to provide document lists in accordance with terms of the inferred information.
In accordance with one aspect of the invention is a method of fulfilling an information need. An input query is obtained. The input query includes at least one user-specified search term. The input query is converted into a converted input query. The converted input query is used to obtain a result wherein said result does not include said at least one user-specified search term included in said input query.
In accordance with another aspect of the invention is a data structure stored in a computer memory. The data structure includes: at least one key field describing an input query format, and at least one of: a statement format field specifying an alternate form in which data included in said input query format may be specified as an affirmative statement; and a question format field specifying data included in said input query format as a question.
In accordance with another aspect of the invention is a method for determining a result to an input query. It is determined whether the input query matches an input query format. If the input query matches the specified input query format, at least one alternate form is determined in which data included in the input query format may be specified as at least one of: an affirmative statement of a question and a question. The result is determined using the at least one of said affirmative statement and the question. The result does not include user-specified search terms of said input query.
In accordance with yet another aspect of the invention is a computer program product for fulfilling an information need comprising: executable code that obtains an input query including at least one user-specified search term; executable code that converts said input query into a converted input query; and executable code that uses said converted input query to obtain a result wherein said result does not include said at least one user-specified search term included in said input query.
In accordance with another aspect of the invention is a computer program product for determining a result to an input query comprising: executable code that determines whether said input query matches an input query format; executable code that, if said input query matches said specified input query format, determines at least one alternate form in which data included in said input query format may be specified as at least one of: an affirmative statement of a question and a question; and executable code that determines said result using said at least one of said affirmative statement and said question, said result not including user-specified search terms of said input query.
In accordance with another aspect of the invention is a method of fulfilling an information need not formulated as a natural language question. A query is accepted that includes one or more words not formulated as a natural language question but which corresponds to an information need. One or more answer are returned that satisfy the information need.
Features and advantages of the present invention will become more apparent from the following detailed description of exemplary embodiments thereof taken in conjunction with the accompanying drawings in which:
Described herein are techniques used for producing answers and optionally documents corresponding to a query which is may not be formulated as a question.
Referring now to
Referring to
It should be noted that an embodiment may display results as an “answer” in any one of a variety of different forms and formats. As an example, in contrast to the affirmative statement answer format 67a of
It should be noted that the techniques described in following paragraphs may be used to infer, for example, a question, from an input query not in the form of a natural language question. These techniques may also be used to infer other forms of information need from the input query such as, for example, alternative affirmative statements.
Referring now to
Each of the user systems 614a-614n and the query server system 612 included in the computer system 610 may be connected to the communication medium 618 by any one of a variety of connections as may be provided and supported in accordance with the type of communication medium 618. The processors included in the user computer systems 614a-614n and the query server system 612 may be any one of a variety of commercially available single or multi-processor system, such as an Intel-based processor, IBM mainframe or other type of commercially available processor able to support incoming traffic in accordance with each particular embodiment and application.
It should be noted that the particulars of the hardware and software included in one embodiment of the user systems 614a-614n and the query server system 612 are described herein in more detail. However, the particulars may vary in accordance with each embodiment. Each of the user computers 614a-614n, as well as the query server system 612, may all be located at the same physical site, or, alternatively, may also be located in different physical locations. Examples of the communication medium that may be used to provide the different types of connections between the user computer systems and the query server system of the computer system 610 may use a variety of different communication protocols such as SCSI, ESCON, Fibre Channel, or GIGE (Gigabit Ethernet), and the like. Some or all of the connections by which the user systems 614a-614n and the query server system 612 may be connected to the communication medium 618 may pass through other communication devices, such as a Connectrix or other switching equipment that may exist such as a phone line, a repeater, a multiplexer or even a satellite.
Referring now to
In one example, a graphical user interface (GUI) may be displayed on an output device of the user system 614a, such as a terminal with a display screen. A data query may be input, as by a keyboard and/or mouse, for example, using the GUI. The data query may be communicated to the query server system 612 over the connection 618, such as the Internet. The results accordingly may be communicated from the query server system to the user system 614a and displayed on an output device of the user system 614a The GUI may be as described, for example, in connection with
Referring now to
As with the user system 614a, the query server system 650 may be any one of variety of different configurations of hardware and/or software components determined in accordance with the parameters of the particular server system. For example, a server system embodiment may not include a router and may include only a single system, such as 654a connected to data storage 660.
Referring now to
It should be noted that the input query may be processed to obtain both the documents at step 86 and the answers at step 90 such that the documents and answers may be output and displayed as a single set of query results 92. An embodiment may alternatively output only one of the documents or answers as the query results. Additionally, an embodiment may query documents using the inferred answer, or in accordance with the original input query, and/or variations thereof.
Referring now to
Referring now to
The CONCEPTS EXTRACTION and SYNTAX ANALYIS module as referenced, for example, in
Referring now to
It should be noted that although a finite state machine is used to represent the analyzed query, other representations may be used.
As described above,
The weight of an analysis may be computed as the sum of the weight of each of its components. For example, the weight of the analysis capital of LOCATION is 2400 (1000+100+400), the sum of the weight of capital, 1000, the weight of the word of, 1000 and the weight of LOCATION, 400. Although the Finite State Machine is one representation of the different alternative analysis results, the analysis result alternatives may be listed instead as follows:
Processing steps that may be performed by the CONCEPT EXTRACTION AND SYNTAX ANALYSIS module are described in the pending U.S. patent application Ser. No. 09/559,223, filed Apr. 26, 2000, entitled SYSTEM FOR FULFILLING AN INFORMATION NEED. It should be noted that in this embodiment, the weights may be stored with the associated arc values, for example, as shown in
Referring now to
In this example, the representation 1000 includes a set of entries 1002 and 1004. Each ENTRY includes the fields: KEYS, STATEMENTS, QUESTIONS and SYNONYMS STATEMENTS. Other embodiments may also include other fields with various information. The KEY fields represent possible alternative ways that the information need may be set forth in an input query rather than in the form of a question. As described elsewhere herein, if an input query matches one of the KEY fields, it may be inferred that the user's information need is related to the answer to a question. The STATEMENTS fields represent possible alternative ways in which the same information need may be set forth in affirmative statements. The QUESTIONS fields correspond to possible questions which convey the same information need (see the Question Answering application). The SYNONYMS STATEMENTS fields represents synonym variations of the STATEMENTS.
Each ENTRY may include alternative representations and forms of a set of related terms used to express an information need conveyed in an input query. For example, the relationship capital of, represents a relationship between a city and a country. Possible, STATEMENTS of such relationship are:
The above information is associated with the STATEMENTS portion of the ENTRY.
Possible synonyms statements are
The above information is associated with the SYNONYMS STATEMENTS.
Similarly, possible questions for the relationship are
The above information is associated with the QUESTIONS portion of the ENTRY.
Additionally, the following are ways to express the information need, as may be set forth in the input query, without formulating a question as may be set forth in the QUESTIONS fields:
The Structure Repository may be characterized as including information about the concepts, relationships and syntactic structures of a language and various terms. The information included in the Structures Repository may be determined manually prior to processing a data query.
Referring now to
Referring now to
At step 2002, a first ENTRY is read from the Structures Repository. At step 2004, a variable KEY is assigned the first of the KEYS for the current ENTRY. At step 2006, a variable CURR_QUERY is assigned an analyzed query alternative. Recall that an analyzed query alternative includes terms associated with transitions specified previously in connection with the finite state machine from a start to an end node. At step 2008, a determination is made as to whether the current analyzed query alternative matches the current KEY. If so, control proceeds to step 2010 where information about the match, such as the weight, is saved. Control proceeds to step 2012. If the match fails at step 2008, control proceeds to step 2012 without step 2010 processing. At step 2012, the CURR_QUERY is assigned the next analyzed query alternative. At step 2014, a determination is made as to whether all the analyzed query alternatives have been compared to the current KEY. If not, control proceeds to step 2008. Otherwise, control proceeds to step 2016 where the next KEY from the current ENTRY is obtained. At step 2018, a determination is made as to whether all KEYS of the current ENTRY have been processed. If not, control proceeds to step 2006. Otherwise, control proceeds to step 2020 where the next ENTRY is read from the repository. At step 2022, a determination is made as to whether all the ENTRY structures from the repository have been processed. If so, processing stops. Otherwise, control proceeds to step 2004.
What will now be described is an example of how the foregoing method steps of flowchart 2000 may be used to match an analyzed query against ENTRY information from the Structure Repository of
The first Entry of the Structures Repository is considered, and the two KEYS of this entry
The concept COUNTRY matches the input word Pakistan and this word is recorded in the match. Multiple words may be associated with a concept and recorded in connection with match processing. For example the Duchy of Luxembourg match the concept COUNTRY, and the four words the Duchy of Luxembourg are associated with COUNTRY. The KEY and the associated matching words with its weight are added to the set of matched and records, for example, as recorded as step 2010.
Processing proceeds until attempts are made to match the keys of all entries. Then, the key with the highest weight is selected (if there is more than one key with the highest weight, one of those keys is chosen). In our example, the key capital of COUNTRY (Pakistan) is returned as best match key.
The STRUCTURES REPOSITORY KEY MATCH MODULE, as described above, produces as an output a best matched key determined in accordance with the input query. The best matched key may then be an input to the MAPPING OF KEY TO PARTIALLY SPECIFIED QUERIES MODULE which converts this best matched key to one or more partially specified queries. The MAPPING OF KEY TO PARTIALLY SPECIFIED QUERIES MODULE proceeds by selecting the STATEMENTS associated with the entry in the Structures repository corresponding to the given best key. Subsequently, the concepts specified in the input query which are associated with words in the key are substituted instead of the corresponding concepts into the statements. The remaining concepts which are not associated with any word in the statements are then converted into the corresponding partially unspecified query with the restriction associated with the concept.
Consider the following example. If the key with the associated words is:
using the Structure repository shown in
The remaining concepts are converted into partially unspecified portions with their corresponding restriction, in this case CITY is replaced by _[CITY] which is a partially unspecified portion which matches any city. This process produces the following partially unspecified queries:
Referring now to
Referring now to
Processing within the MAPPING OF KEY TO QUESTION MODULE is similar to the processing described elsewhere herein in connection with the MAPPING OF KEY TO PARTIALLY SPECIFIED QUERIES MODULE. However, the MAPPING OF KEY TO QUESTION MODULE selects questions from the QUESTIONS entry field rather than the STATEMENTS entry field.
For example, if the key with the associated words is:
using the Structure repository shown in
Is selected since capital of COUNTRY matches on of its key, capital of COUNTRY. The corresponding questions are selected:
Then the words associated with concepts or phrases in the key are substituted to the statements, i.e. Pakistan is substituted for COUNTRY in the statements to produce questions:
What will now be described are method steps for processing an input query to produce an answer using the foregoing ENTRY Structures.
Referring now to
At step 1202, an input query is obtained, for example, as by using a graphical user interface with an input device as described elsewhere herein. At step 1204, CONCEPTS EXTRACTION and SYNTAX ANALYSIS is performed to produce the analyzed query 1206. The Structures Repository 1210 is searched at step 1208 to determine whether there is a match of the input query with a KEY included in a defined ENTRY. If, at step 1212, it is determined that there is no match of an ENTRY for the input query, control proceeds to step 1214 where output may be produced indicating that no match has been found. If, at step 1212, it is determined that at least one match has been found, control proceeds to step 1224 where the best match item is selected, for example, based on predetermined weights.
Control proceeds to step 1225 where further processing continues in accordance with the type of match. In this example, the type may be one of KEY or QUESTION. If the type is KEY, control proceeds to step 1216 where a mapping of the key to partially specified queries is performed to produce the partially specified queries 1218. The partially specified queries 1218 are input to the Information Need Fulfilling Engine 1220 to produce answers 1222. An embodiment utilizing partially specified questions and processing as may be performed by the Information Need Fulfilling Engine are described in, for example, pending U.S. patent application Ser. No. 09/559,223, filed Apr. 26, 2000, entitled SYSTEM FOR FULFILLING AN INFORMATION NEED and pending U.S. patent application Ser. No. 10/004,952, filed Dec. 5, 2001, entitled SYSTEM FOR FULFILLING AN INFORMATION NEED USING AN EXTENDED MATCHING TECHNIQUE. Other embodiments may specify queries in other formats having different capabilities in connection with searching.
If the type is a QUESTION, the question 1226 is input to a Questions Answering Engine 1228 to output the Answers 1230. It should be noted that an embodiment of the Questions Answering Engine is described, for example, in pending U.S. patent application Ser. No. 09/845,571, filed Apr. 30, 2001, entitled SYSTEM FOR ANSWERING NATURAL LANGUAGE QUESTIONS. Other embodiments may utilize other Questions Answering Engines.
The STRUCTURES REPOSITORY KEY MATCH MODULE, as referred to, for example, in
Each alternative of the analyzed query is compared against each of the KEYS of each Entry found in the Structure Repository. If there is a match, the match is recorded with the associated weight. Once all Keys have been compared to all possible alternatives of the analyzed query, the match with the highest weight is identified as the best match (if there is more than one match with the highest weight, one match is chosen either randomly or through some other heuristics). If no match is found in the KEYS, the module returns no match.
The matching of the analyses against a particular one of the KEYS may be performed in a variety of different ways. An embodiment may perform a term by term comparison of each analysis alternative against each term included in each of the KEYS. An embodiment may also identify whether a particular one of the KEYS is recognizable by the finite state machine, for example, by using a KEY as input to the finite-state machine.
Referring now to
The Information Needs Processing Module 3004 performs CONCEPTS EXTRACTION AND SYNTAX ANALYSIS to produce an Analyzed Query. The Analyzed Query is input to the CONVERSION TO INFORMATION NEED QUERY processing to output partially specified queries. The partially specified queries are input to the INFORMATION NEED FULFILLING ENGINE that outputs Answers 3016.
The Question and Answering Processing Module 3006 performs CONCEPTS EXTRACTION AND SYNTAX ANALYSIS to produce an Analyzed Query. The Analyzed Query is input to the CONVERSION TO QUESTIONS processing to output Questions. The Questions are input to the QUESTION ANSWERING ENGINE that outputs Answers 3016.
Using the techniques described herein, an input query may be analyzed to infer a user information need that may not be explicitly set forth in the input query. Described herein as an example is an input query that is not in the form of a question. By analyzing the input query, a question in one or more variations may be formulated to derive the underlying user request. That is, the user may be seeking the answer to a question formulated from search query terms not in the form of a question. Analyzed input request results may also be used to formulate one or more affirmative statements to obtain derivative user information not explicitly set forth in the input query. Accordingly, documents may be searched based on the obtained derivative information, such as, for example, the answer to the formulated questions, or a term in an affirmative statement. The user information need may be determined without using predetermined tags
Referring back to
An ENTRY structure in an embodiment may also include other portions than as set forth in
An embodiment of the ENTRY structure may also include the following elements defined at the same level as the STATEMENTS, SYNONYMS STATEMENTS and
Using the foregoing statements in the APPLICATION STATEMENT section, an application may be invoked in connection with performing searching or other operations. The particular application invoked, such as APPLICATION1_NAME, may take as input one or more parameters, such as PARAM1. The parameters may also be output parameters by which the application communicates return information. The parameters may include search terms and other information in accordance with the particular application being invoked.
An embodiment may also include the following elements defined at the same level as the STATEMENTS, SYNONYMS STATEMENTS and QUESTIONS portions:
APPLICATION STATEMENTS
The foregoing may be used to provide for conditional execution or invocation of an application with evaluation of conditions in a particular order. CONDITION1 may be evaluated in accordance with the specified optional VALUE causing APPLICATION1_NAME to be executed. An embodiment may evaluate all the conditions and invoke one or more applications in accordance with the evaluation. An embodiment may also choose not to continue evaluation of conditions and invocation of applications once a first application has been executed.
The structure set forth in
While the invention has been described and illustrated in connection with certain preferred embodiments, many variations and modifications as will be evident to those skilled in the art may be made therein without departing from the spirit of the invention, and the invention is thus not to be limited to the precise details of construction set forth above.
| Number | Date | Country | |
|---|---|---|---|
| 60333318 | Nov 2001 | US | |
| 60200766 | Apr 2000 | US | |
| 60251608 | Dec 2000 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 10305221 | Nov 2002 | US |
| Child | 11490719 | Jul 2006 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 09559223 | Apr 2000 | US |
| Child | 11490719 | Jul 2006 | US |
| Parent | 09845571 | Apr 2001 | US |
| Child | 11490719 | Jul 2006 | US |
| Parent | 10004952 | Dec 2001 | US |
| Child | 10305221 | US | |
| Parent | 09559223 | Apr 2000 | US |
| Child | 10305221 | US |
