Integrating relation and keyword matching in information retrieval

Authors:
Tanveer J. Siddiqui;Uma Shanker Tiwary
Affiliations:
J.K. Institute of Applied Physics and Technology, Department of Electronics & Communication, University of Allahabad, Allahabad, India;Indian Institute of Information Technology, Allahabad
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Year:
2005

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Abstract

We propose an information retrieval (IR) model that combines relation and keyword matching. The model relies on a novel algorithm for relation matching. The algorithm takes the advantage of any existing relational similarity between document and query to improve retrieval effectiveness. If query concepts(terms) appearing in a document exhibit similar relationship then the proposed similarity measure will give high rank to the document as compared to those in which query terms exhibit different relationship. A conceptual graph (CG) representation has been used to capture relationship between concepts. In order to keep the approach computationally simple a simplified form of CG matching has been used instead of graph derivation. Structural variations have been captured during matching through simple heuristics. CG similarity measure proposed by us is simple, flexible and scalable and can find application in many related tasks like information filtering, question answering, document summarization etc.