A Knowledge-Based Multi-Agent Approach for Initial Query Refinement in Information Retrieval
Tatyana Ivanova, I. M. Momtchev · 2010
Query refinement is one of the main approaches for overcoming natural language lexical ambiguity and improving the quality of search results in Information Retrieval. In this paper we propose a knowledge–rich personalized approach for iterative query reformulation before sending it to search engines and entropybased approach for refinement quality estimation. The underling hypothesis is that the query reformulation entropy is a valuable characteristic of the refinement quality. We use multi-agent architecture to implement our approach. Experimental results confirm that there is a trend for significant improvement in the quality of search results for large values of entropy.