System for classifying a search query
First Claim
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1. A method of classifying a search query with a computer having a processor, the method comprising:
- categorizing, by the processor, a plurality of selected search queries;
storing the categorized search queries in a taxonomy database according to category, the taxonomy database being stored in a data storage system coupled with the processor;
storing in a query log database query log data derived from the plurality of categorized search queries submitted to one or more search engines and including user click data, wherein the query log database is stored in the data storage system and is coupled with the processor;
computing, by the processor, a term vector for each of the plurality of selected search queries as a function of a web search, wherein the data storage system is operable to store the term vectors;
creating, by the processor, a classifier function as a function of the computing the term vectors, wherein the data storage system is operable to store the classifier function;
regularizing, by the processor, the classifier function based on the query log data comprising;
constructing a weighted query graph including nodes that represent the plurality of categorized search queries to model semantic relationships therebetween based on the query log data; and
mapping the weighted query graph to a line such that related queries are located close to each other within the weighted query graph; and
classifying, by the processor, an un-categorized search query as a function of the regularized classifier function.
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Abstract
A system is described for classifying a search query. The system may create a machine learning classifier function that may be “trained” by a plurality of categorized queries within a query taxonomy. The system may represent the queries as term vectors and input the term vectors to the machine learning classifier function to generate a value that may correspond to a particular category within the query taxonomy. The system may regularize the machine learning classifier function based on user search click data to improve the classifying accuracy.
93 Citations
21 Claims
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1. A method of classifying a search query with a computer having a processor, the method comprising:
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categorizing, by the processor, a plurality of selected search queries; storing the categorized search queries in a taxonomy database according to category, the taxonomy database being stored in a data storage system coupled with the processor; storing in a query log database query log data derived from the plurality of categorized search queries submitted to one or more search engines and including user click data, wherein the query log database is stored in the data storage system and is coupled with the processor; computing, by the processor, a term vector for each of the plurality of selected search queries as a function of a web search, wherein the data storage system is operable to store the term vectors; creating, by the processor, a classifier function as a function of the computing the term vectors, wherein the data storage system is operable to store the classifier function; regularizing, by the processor, the classifier function based on the query log data comprising; constructing a weighted query graph including nodes that represent the plurality of categorized search queries to model semantic relationships therebetween based on the query log data; and mapping the weighted query graph to a line such that related queries are located close to each other within the weighted query graph; and classifying, by the processor, an un-categorized search query as a function of the regularized classifier function. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system for creating a regularized classifier function for classifying a search query comprising:
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a taxonomy database operable to store a plurality of categorized search queries wherein the taxonomy database is stored in a data storage system; a term vector processor coupled with the taxonomy database and operable to create term vectors for each of the plurality of categorized search queries as a function of a web search, wherein the data storage system is operable to store the term vectors and is coupled with the term vector processor; a classifier function processor coupled with the term vector processor and operable to create a classifier function as a function of the term vectors, wherein the data storage system is operable to store the classifier function and is coupled with the classifier function processor; a query log database containing query log data derived from the plurality of categorized search queries submitted to one or more search engines and including user click data, wherein the query log database is stored in the data storage system; and a regularization processor coupled with the classifier function processor and the data storage system, the regularization processor operable to regularize the classifier function by; constructing a weighted query graph including nodes that represent the plurality of categorized search queries to model semantic relationships therebetween based on the query log data; and regularizing the machine learning classifier function based on the query log data by mapping the weighted query graph to a line such that related queries are located close to each other within the weighted query graph. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18)
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19. A system for classifying a search query comprising computer programming logic stored in a memory and executable by a processor coupled with the memory, the computer programming logic comprising:
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first logic operative to compute term vectors as a function of categorized search queries in a query taxonomy; second logic coupled with the first logic and operative to generate a vector space as a function of the term vectors; third logic coupled with the second logic and operative to create a classifier function as a function of the vector space; fourth logic coupled with the third logic and operative to regularize the classifier function, wherein the fourth logic; constructs a weighted query graph including nodes that represent the categorized search queries to model semantic relationships therebetween based on query log data derived from submission of the categorized search queries to one or more search engines and including user click data; and regularizes the classifier function based on the query log data by mapping the weighted query graph to a line such that related queries are located close to each other within the weighted query graph; and fifth logic coupled with the fourth logic and operative to classify an un-categorized search query as a function of the regularized classifier function. - View Dependent Claims (20, 21)
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Specification