Efficient passage retrieval using document metadata

Abstract

A system, method and computer program product for efficiently retrieving relevant passages to questions based on a corpus of data. A processor device receives an input query and performs a query analysis to obtain searchable query terms. The processor performs: matching metadata associated with one or more documents against the query terms. The document metadata includes one or more of: a title of the documents, one or more user tags or clouds. Then the processor device performs: mapping matched document metadata to corresponding one or more documents; identifying corresponding matched documents to form a subcorpus of documents; and conducting a search in the data subcorpus using the searchable query terms to obtain one or more passages relevant input query from the identified documents.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]The present invention relates to and claims the benefit of the filing date of commonly-owned, co-pending U.S. Provisional Patent Application No. 61 / 386,019, filed Sep. 24, 2010, the entire contents and disclosure of which is incorporated by reference as if fully set forth herein.BACKGROUND[0002]The invention relates generally to information retrieval systems, and more particularly, the invention relates to an automated query / answer system and method implementing a passage retrieval component to conduct a search that identifies passages relevant to a given question using document metadata from a collection including text-based resources.DESCRIPTION OF THE RELATED ART[0003]An introduction to the current issues and approaches of question answering (QA) can be found in the web-based reference http: / / en.wikipedia.org / wiki / Question_answering. Generally, QA is a type of information retrieval. Given a collection of documents (such as the World Wi...

AI Technical Summary

Benefits of technology

[0010]In one aspect there is provided a computing infrastructure and methodology that conducts question and answering and performs automatic passage retrieval operations in a highly efficient manner.

[0011]In one aspect, there is provided a computer-implemented method for efficiently retrieving relevant passages to questions based on a corpus of data comprising: receiving an input query; performing a query context analysis upon the input query to obtain searchable query terms; matching metadata associated with one or more documents against the query terms; mapping matched document metadata to corresponding one or more documents; identifying corresponding matched documents to form a subcorpus of documents; and conducting a search in the data subcorpus using the searchable query terms to obtain one or more passages relevant to the input query from the identified documents, wherein one or more processor devices performs one or more the retrieving, performing, matching, mapping, identifying and conducting.

[0014]In an alternate embodiment, there is provided a computer-implemented method for efficiently retrieving relevant passages to questions based on a corpus of data comprising: receiving, at a processor device, an input query; performing, at the processor device, a query context analysis upon the input query to obtain searchable query terms; accessing a dictionary of document metadata obtained from one or more documents of the data corpus, each stored document metadata being associated with a corresponding document identification (ID); performing, by the processor device, a dictionary matching of the metadata associated with one or more documents against the query terms; mapping matched document metadata to corresponding one or more document IDs; identifying corresponding matched documents to form a subcorpus of documents; and conducting a search in the subcorpus using the searchable query terms to obtain passages relevant to the input query from the identified documents.

Problems solved by technology

A major unsolved problem in such information query paradigms is the lack of a computer program capable of accurately answering factual questions based on information included in a collection of documents that can be either structured, unstructured, or both.

It is a challenge to understand the query, to find appropriate documents that might contain the answer, and to extract the correct answer to be delivered to the user.

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