Semantic query expansion for fuzzy proximity information retrieval model

Abstract

Aims and Objectives of the Research Our research aim is to ameliorate the recall of the Fuzzy Proximity Information Retrieval Model (FPIRM) of Beigbeder & Mercier (2005), their approach is very “precise” when evaluating internationally agreed upon collections of documents used for benchmarking. The precision in this case for each query is the ratio of relevant documents retrieved over documents returned. However, the recall is weak. By recall we mean the ratio of relevant documents retrieved over all relevant documents in the collection (Rijsbergen, 1979). FPIRM approach evaluates the relevance between a document and a query by using a fuzzy function that takes into account the distance between the occurrences of query terms in a document. Our research studies the use of semantic query expansion to increase the recall of their model.

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Our testbed is the collection INEX3 2009, which contains all English articles of Wikipedia 2008 (2’600’000 documents). These documents are annotated using YAGO. We are considering the use of this ontology to find new terms that are semantically related to query terms.

Research Results to Date During our study, we’ve experimented with the use of the lexical thesaurus WordNet, where we looked up all synonyms of each term in the query. This trivial use of WordNet produced the query drift. This is a common issue related to query expansion and caused by the “alteration of the focus of a search topic” (Mitra, Singhal, & Buckley, 1998) . Figure 1 shows how query expansion using only WordNet synonyms affected the performance of the fuzzy proximity model. 3 INEX (INitiative for the Evaluation of XML retrieval) an information retrieval evaluation forum

References

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