Fuzzy Networks based Information Retrieval Model

Abstract

We describe an Information Retrieval Model based on fuzzy Networks that incorporates dependence relationships between indexing terms. We details the design and implementation of a new Information Retrieval Model based on Fuzzy Network. From this Network, most relevant term to term dependence relationships are extracted using within document terms dependency analyses. The criteria used to select these dependence relationships are the strength of dependency of each pair of terms within each document and the strength of dependency of each pair of terms in the entire document collection. The relevance of a document to a query is interpreted by two degrees: the necessity and the possibility. The necessity degree evaluates the extent to which a document is relevant to a query, whereas the possibility degree evaluates the reasons of eliminating irrelevant documents. These two measures are also used for quantifying terms-terms links and terms-documents links. Experiments carried out on three standard document collections show the effectiveness of the model.