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A User-Aware and Semantic Approach for Enterprise Search

A User-Aware and Semantic Approach for Enterprise Search

Giacomo Cabri, Riccardo Martoglia
Copyright: © 2020 |Pages: 20
ISBN13: 9781799809517|ISBN10: 179980951X|EISBN13: 9781799809524
DOI: 10.4018/978-1-7998-0951-7.ch016
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MLA

Cabri, Giacomo, and Riccardo Martoglia. "A User-Aware and Semantic Approach for Enterprise Search." Natural Language Processing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2020, pp. 302-321. https://doi.org/10.4018/978-1-7998-0951-7.ch016

APA

Cabri, G. & Martoglia, R. (2020). A User-Aware and Semantic Approach for Enterprise Search. In I. Management Association (Ed.), Natural Language Processing: Concepts, Methodologies, Tools, and Applications (pp. 302-321). IGI Global. https://doi.org/10.4018/978-1-7998-0951-7.ch016

Chicago

Cabri, Giacomo, and Riccardo Martoglia. "A User-Aware and Semantic Approach for Enterprise Search." In Natural Language Processing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 302-321. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-0951-7.ch016

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Abstract

This article describes how in addition to general purposes search engines, specialized search engines have appeared and have gained their part of the market. An enterprise search engine enables the search inside the enterprise information, mainly web pages but also other kinds of documents; the search is performed by people inside the enterprise or by customers. This article proposes an enterprise search engine called AMBIT1-SE that relies on two enhancements: first, it is user-aware in the sense that it takes into consideration the profile of the users that perform the query; second, it exploits semantic techniques to consider not only exact matches but also synonyms and related terms. It performs two main activities: (1) information processing to analyse the documents and build the user profile and (2) search and retrieval to search for information that matches user's query and profile. An experimental evaluation of the proposed approach is performed on different real websites, showing its benefits over other well-established approaches.

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