Automated relevance tuning
First Claim
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1. A method for performing a document search, comprising:
- providing a plurality of documents, each document being associated with at least one search query;
identifying one or more feature parameters for use in a document ranker, each feature parameter having an initial parameter value;
ranking each of the plurality of documents relative to a test set of documents at each of a plurality of parameter variations using said document ranker, wherein each parameter variation comprises a parameter value for an associated feature parameter and the initial parameter value for all other feature parameters;
determining, for each of the plurality of documents, one or more parameter variations that produce a ranking change for a document relative to one or more of the test documents;
aggregating, for each feature parameter, the ranking changes for each of the plurality of documents for each parameter variation associated with the feature parameter;
identifying, for each feature parameter, a parameter variation corresponding to a maximum relevance value based on the aggregated ranking changes for each of the plurality of documents;
adjusting the parameter values of the plurality of parameters based on the identified parameter variations corresponding to the maximum relevance values;
receiving a search query; and
calculating a ranking value for at least one document using the adjusted parameter values in response to the search query.
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Abstract
A system and method for optimizing the performance of a document ranker in a search engine. Weights are assigned to the document features considered by the document ranker. The weights are optimized to produce the highest possible relative ranking for a group of test documents in response to an associated group of search queries.
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Citations
20 Claims
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1. A method for performing a document search, comprising:
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providing a plurality of documents, each document being associated with at least one search query;
identifying one or more feature parameters for use in a document ranker, each feature parameter having an initial parameter value;
ranking each of the plurality of documents relative to a test set of documents at each of a plurality of parameter variations using said document ranker, wherein each parameter variation comprises a parameter value for an associated feature parameter and the initial parameter value for all other feature parameters;
determining, for each of the plurality of documents, one or more parameter variations that produce a ranking change for a document relative to one or more of the test documents;
aggregating, for each feature parameter, the ranking changes for each of the plurality of documents for each parameter variation associated with the feature parameter;
identifying, for each feature parameter, a parameter variation corresponding to a maximum relevance value based on the aggregated ranking changes for each of the plurality of documents;
adjusting the parameter values of the plurality of parameters based on the identified parameter variations corresponding to the maximum relevance values;
receiving a search query; and
calculating a ranking value for at least one document using the adjusted parameter values in response to the search query. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method for recognizing a pattern, comprising:
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providing a plurality of patterns, each pattern being associated with at least one pattern query;
identifying one or more feature parameters for use in a pattern ranker, each feature parameter having an initial parameter value;
ranking each of the plurality of patterns relative to a test set of patterns for each of a plurality of parameter variations using said pattern ranker, wherein each parameter variation comprises a parameter value for an associated feature parameter and the initial parameter value for all other feature parameters;
determining, for each of the plurality of patterns, one or more parameter variations that produce a ranking change for a pattern relative to one or more of the test patterns;
aggregating, for each feature parameter, the ranking changes for each of the plurality of patterns for each parameter variation associated with the feature parameter;
identifying, for each feature parameter, a parameter variation corresponding to a maximum relevance value based on the aggregated ranking changes for each of the plurality of patterns;
adjusting the parameter values of the plurality of parameters based on the identified parameter variations corresponding to the maximum relevance values;
receiving a pattern query; and
calculating a ranking value for at least one pattern using the adjusted parameter values in response to the pattern query. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A system for performing document searches, comprising:
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a document feature evaluator for determining one or more document feature values for a document based on a search query;
a document ranker for calculating a ranking value based on the one or more document feature values and a feature parameter value associated with each document feature;
a document ranking aggregator for aggregating document ranking information, identifying variations in feature parameter values corresponding to ranking changes between two or more documents, and determining variations in feature parameter values corresponding to maximum relevance values for a collection of documents; and
a parameter optimizer for modifying the feature parameter values based on the variations corresponding to maximum relevance values for the collection of documents. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification