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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Information Retrieval (IR) and Extracting Associative Rules

Information Retrieval (IR) and Extracting Associative Rules
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Author(s): Asmae Dami (Sultan Moulay Slimane University, Morocco), Mohamed Fakir (Sultan Moulay Slimane University, Morocco)and Belaid Bouikhalene (Sultan Moulay Slimane University, Morocco)
Copyright: 2016
Pages: 20
Source title: Business Intelligence: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-9562-7.ch037

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Abstract

This chapter is located in the intersection of two research themes, namely: Information Retrieval and Knowledge Discovery from texts (Text mining). The purpose of this paper is two-fold: first, it focuses on Information Retrieval (IR) whose purpose is to implement a set of models and systems for selecting a set of documents satisfying user needs in terms of information expressed as a query. An information retrieval system is composed mainly of two processes the representation and retrieval process. The process of representation is called indexing, which allows representation of documents and queries by descriptors, or indexes. These descriptors reflect the contents of documents. The retrieval process consists on the comparison between documents representations and query representation. The second aim of this paper is to discover the relationships between terms (keywords) descriptors of documents in a document database. The correlations (relationships) between terms are extracted by using a technique of the Text mining, mainly association rules.

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