A Structured Indexing Model Based on Noun Phrases

Abstract — Most of the indexing models are based on simple independent words, also known as key words. This approach does not take account of the context as well as the relations between the words. Therefore, the precision of system is limited. In this article, we present a structured indexing model based on noun phrases to increase the precision of an Information Retrieval System (IRS). In this model, we used a grammatical parser to extract and structure a noun phrase in determining the various roles of the words of a noun phrase and their syntactic relations. We represent the set of the index terms of query in the form of Bayesian networks which enables us to calculate the matching function between a query and a document. We carried out experiments to test this model. That the positive results obtained encourages us to continue in this direction. Index Terms—Bayesian network, indexing model, information retrieval, natural language processing. M I