DYNAMIC METADATA FILTERING FOR CLASSIFIER PREDICTION
First Claim
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1. A method to be executed at least in part in a computing device for predicting query results in a document search system utilizing metadata properties, the method comprising:
- receiving a metadata property table;
receiving a classifier model table;
joining the metadata property table and the classifier model table;
applying a filter condition to the joined table based on user-specified query conditions;
obtaining a list of documents satisfying the filter condition;
computing a probability of a document satisfying a user-specified query based on the list of documents; and
presenting the probability to the user.
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Abstract
A classifier is used to predict relevant results with arbitrary filtering conditions specified by the user. The classifier model is stored as a database table and joined with a metadata properties table instead of calculating the query result probability using the full classifier model. A user-specified query based filter is applied to the joined tables to obtain the list of documents satisfying the filter. The probability is then computed using the sub-model.
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Citations
20 Claims
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1. A method to be executed at least in part in a computing device for predicting query results in a document search system utilizing metadata properties, the method comprising:
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receiving a metadata property table; receiving a classifier model table; joining the metadata property table and the classifier model table; applying a filter condition to the joined table based on user-specified query conditions; obtaining a list of documents satisfying the filter condition; computing a probability of a document satisfying a user-specified query based on the list of documents; and presenting the probability to the user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. The method of claim 10, wherein the probability is computed using:
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where term probabilities (termprob) are derived from raw counts of a training data set associated with the classifier model.
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11. A system for predicting query results in a document search system utilizing metadata properties, the system comprising:
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a memory; a processor coupled to the memory, capable of executing; a service application configured to; receive a user defined metadata schema; generate a metadata property table based on the received schema; a prediction engine configured to; receive a classifier model table based on training data associated with documents stored by the document search system; join the metadata property table and the classifier model table; apply a filter condition to the joined table based on user-specified query conditions; obtain a list of documents satisfying the filter condition; and compute a probability of a document satisfying a user-specified query based on the list of documents. - View Dependent Claims (12, 13, 14, 15)
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16. A computer-readable storage medium with instructions encoded thereon for predicting query results in a document search system utilizing metadata properties, the instructions comprising:
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receiving custom metadata schema; generating a metadata property table based on the received schema; receiving a classifier model matrix based on a training data set associated with documents processed by the system; generating a classifier model table from the sparse classifier model matrix; joining the metadata property table and the classifier model table; applying at least one filter condition to the joined table based on user-specified query conditions; obtaining a list of documents satisfying the at least one filter condition; and computing a probability of a document satisfying a user-specified query based on the list of documents. - View Dependent Claims (17, 18, 19, 20)
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Specification