Semantic / Fuzzy Information Retrieval System

Semantic / Fuzzy Information Retrieval System

Mounira Chkiwa, Anis Jedidi, Faiez Gargouri
DOI: 10.4018/IJITWE.2017010103
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

In this paper, the authors present an overall description of their information retrieval system which makes a practical collaboration between Semantic Web and Fuzzy logic in order to have profit from their advantages in the information retrieval domain. Their system is dedicated for kids, for this reason the semantic/fuzzy collaboration materialized must be in the background of the information retrieval process because such category of users cannot certainly control semantic web technologies neither fuzzy logic commands. In this paper, the authors present the different services proposed by their system and how they use Semantic Web and Fuzzy logic to develop it. Evaluation tests of the system using universal measures show clearly its efficiency.
Article Preview
Top

1. Introduction

Retrieving relevant data through the giant amount of web documents represents a daily “challenge” for search engines users especially kids. It begins by a primitive question: “how to express my information need using a set of keywords” and it ends by “which document from the returned set is relevant to me”. To overcome such primordial issues, we present in this paper our information retrieval system dedicated for kids (having mental capabilities that allow them to surf web). Our information retrieval system materializes collaboration between two independent axes: Semantic Web and fuzzy Logic. The expression of the “Semantic Web” was invented by Tim Berners-Lee in 2001 (Berners-Lee et al. 2001); the essential idea is to allow the manipulation of semantic meaning of available data by web software agents via a set of interoperable set of technologies. In a broader context, Fuzzy Logic formalized by Lotfi Zadeh in 1965 (Zadeh, 1965; 1989) is designed to treat cases where imprecision problems occurred. In this context, the fuzzy logic widens the possibilities of description of such problems and allows subsequently to have dedicated solutions for each description. The “human” reasoning of Semantic Web and Fuzzy Logic avails us to exploit them while the development of different services proposed by our information retrieval system. The rest of paper is organized as follows: in the next section we present background technologies employed to develop our system: Fuzzy Logic and Semantic Web. Section 3 presents our contribution; we define therein, two facets of our information retrieval system: option search dedicated for users and services non-transparent to them, those services are conceived to ensure the proposed option search, we enumerate in the same section, some related works and our system particularity. Section 4 presents results of evaluation tests of our system and its comparison with others information retrieval systems dedicated for kids and finally section 5 concludes the paper.

Complete Article List

Search this Journal:
Reset
Volume 19: 1 Issue (2024)
Volume 18: 1 Issue (2023)
Volume 17: 4 Issues (2022): 1 Released, 3 Forthcoming
Volume 16: 4 Issues (2021)
Volume 15: 4 Issues (2020)
Volume 14: 4 Issues (2019)
Volume 13: 4 Issues (2018)
Volume 12: 4 Issues (2017)
Volume 11: 4 Issues (2016)
Volume 10: 4 Issues (2015)
Volume 9: 4 Issues (2014)
Volume 8: 4 Issues (2013)
Volume 7: 4 Issues (2012)
Volume 6: 4 Issues (2011)
Volume 5: 4 Issues (2010)
Volume 4: 4 Issues (2009)
Volume 3: 4 Issues (2008)
Volume 2: 4 Issues (2007)
Volume 1: 4 Issues (2006)
View Complete Journal Contents Listing