Hybrid Query Expansion Model Based on Pseudo Relevance Feedback and Semantic Tree for Arabic IR

摘要

In this paper, the authors propose and readapt a new concept-based approach of query expansion in the context of Arabic information retrieval. The purpose is to represent the query by a set of weighted concepts in order to identify better the user's information need. Firstly, concepts are extracted from the initially retrieved documents by the pseudo-relevance feedback method, and then they are integrated into a semantic weighted tree in order to detect more information contained in the related concepts connected by semantic relations to the primary concepts. The authors use the "Arabic WordNet" as a resource to extract, disambiguate concepts, and build the semantic tree. Experimental results demonstrate that measure of MAP (mean average precision) is about 10 of improvement using the open source Lucene as IR System on a collection formed from the Arabic BBC News.