Methods, systems, and computer program products for integrated world wide web query classification

A system for integrating query categories, comprising:

• a computer processor;
• and
• logic executable by the computer processor, the logic implementing a method, the method including:
• executing a reductionist module on a search query to extract a core term from the search query, the core term used to search a hash table that maps core terms to corresponding categories;
• deriving a first result comprising at least one of the categories from the search of the hash table;
• executing an enrichment module on the search query to yield a second result, the enrichment module including searching an index of terms that are mapped to documents and corresponding categories in the index, the second result indicative of one of the corresponding categories in the index based on a probability score;
• upon determining the core term is present in the hash table, calculating a weighted average for corresponding values of the first result and the second result based on training data acquired from the execution of the reductionist module and the execution of the enrichment module;
• and
• upon determining the core term from the search query is not listed in the hash table, and upon determining the probability score of the one of the corresponding categories in the index for the second result meets a minimum defined confidence value, inserting and storing the core term and the one of the corresponding categories in the hash table and mapping the core term to the one of the corresponding categories in the hash table.

A computer program product embodied on a non-transitory computer readable storage medium, the computer program product including instructions for causing a computer to execute a method for integrating query categories, comprising:

• executing a reductionist module on the search query to extract a core term from the search query, the core term used to search a hash table that maps core terms to corresponding categories;
• deriving a first result comprising at least one of the categories from the search of the hash table;
• executing an enrichment module on the search query to yield a second result, the enrichment module including searching an index of terms that are mapped to documents and corresponding categories in the index, the second result indicative of one of the corresponding categories in the index based on a probability score;
• upon determining the core term is present in the hash table, calculating a weighted average for corresponding values of the first result and the second result based on training data acquired from the execution of the reductionist module and the execution of the enrichment module;
• and
• upon determining the core term from the search query is not listed in the hash table, and upon determining the probability score of the one of the corresponding categories in the index for the second result meets a minimum defined confidence value, inserting and storing the core term and the one of the corresponding categories in the hash table and mapping the core term to the one of the corresponding categories in the hash table.