Method for using dual indices to support query expansion, relevance/non-relevance models, blind/relevance feedback and an intelligent search interface

A system for supporting query expansion, relevance models, non-relevance models and an intelligent search interface using dual indices, the system comprising:

• a computing device comprising a retrieval module and a post-processing module;
• wherein the retrieval module is configured to access an inverted index to obtain an initial retrieval of results in response to a query and to generate a rank list of the results, the results referring to information units (lUs) where the query occurs;
• wherein the post-processing module is configured to:
• determine a number of “N” IUs in the results that are regarded by the computing device as relevant by accessing a forward index;
• determine at least one non-relevant IU in the results that are regarded by the computing device by accessing the forward index;
• and
• use the forward index to perform any one from the group consisting of:
• computing query expansion weights for a top “N” retrieved IUs within the number of “N” IUs, building the relevance models by the contexts of query terms in the top “N” retrieved IUs, building the non-relevance models using the at least one non-relevant IU, and finding the longest contiguous sequences of query terms in the query found in an IU;
• wherein the forward index and inverted index have pointers to locations in the IUs where terms of the query occur more than once, and a forward index and inverted index pointer storage stores the locations in the IUs where the query term occurs only once in the IUs, and the forward index retrieves a term frequency vector of the IU or a set of contexts of the IU;
• and
• wherein the post-processing module is configured to compute query expansion weights for the top “N” retrieved IUs utilizes the forward index to compute query expansion terms by:
• computing at least one relevance query expansion term weight using the top “N” retrieved IUs in the results and the forward index;
• computing at least one non-relevance query expansion term weight using the at least one non-relevant IU in the results and the forward index;
• and
• selecting query expansion terms using the results, the at least one relevance query expansion term weight, and the at least one non-relevance query expansion term weight.

A search engine providing support for query expansion, relevance models, non-relevance models and an intelligent search interface, the search engine comprising:

• a computing device comprising a retrieval module and a post-processing module;
• dual indices consisting of an inverted index and a forward index;
• wherein the retrieval module is configured to access an inverted index to obtain an initial retrieval of results in response to a query, and to generate a rank list of the results, the results referring to information units (IUs) where the query occurs;
• wherein the post-processing module is configured to determine a number of “N” IUs in the results that are regarded by the computing device as relevant by accessing a forward index, determine at least one non-relevant IU in the results that are regarded by the computing device as not relevant by accessing the forward index, and the post-processing module uses the forward index to perform any one from the group consisting of:
• computing query expansion weights for top “N” retrieved IUs, building the relevance models by the contexts of query terms in the top “N” retrieved IUs, building the non-relevance models using the at least one non-relevant IU, and finding the longest contiguous sequences of query terms in the query found in an IU;
• wherein the forward index and inverted index have pointers to locations in the IUs where terms of the query occur more than once, and a forward index and inverted index pointer storage stores the locations in the IUs where the query term occurs only once in the IUs, and the forward index retrieves a term frequency vector of the IU or a set of contexts of the IU;
• and
• wherein computing query expansion weights for a portion of the number of “N” IUs in the results utilizing the forward index to compute query expansion terms by:
• computing at least one relevance query expansion term weight using the portion of the number of “N” IUs in the results and the forward index;
• computing at least one non-relevance query expansion term weight using the at least one non-relevant IU in the results and the forward index;
• and
• selecting query expansion terms using the results, the at least one relevance query expansion term weight, and the at least one non-relevance query expansion term weight.