Assessing web sites quality: A systematic literature review by text and association rules mining

Rim Rekik, Ilhem Kallel, Jorge Casillas and Adel M. Alimi

International Journal of Information Management, 2018, vol. 38, issue 1, 201-216

Abstract: Nowadays society is deeply affected by web content. A web site, regardless of its category, can provide or not for users their needs. To identify its strengths and weaknesses, a process of analyzing and assessing its quality, via some criteria, is necessary. Assessing web sites is considered as a Multiple Criteria Decision Making problem (MCDM), with a massive number of criteria; a reduction phase is needed. This paper presents, firstly a Systematic Literature Review (SLR) to identify the purposes of recent researches from the assessment and determine the affected categories; secondly, it proposes a process of collecting and extracting data (criteria featuring web sites) from a list of studies. Text mining is applied for this SLR to construct a dataset. Then, a method based on Apriori algorithm is assigned and implemented to find association rules between criteria and the category of the web site, and to get a set of frequent criteria. This paper also presents a review on soft computing assessing methods. It aims to help the research community to have a scope in existing research and to derive future developments. The obtained results motivate us to further probe datasets and association rule mining.

Keywords: Assessing web sites; Multiple criteria decision making; Text mining; Association rules mining; Systematic literature review (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:38:y:2018:i:1:p:201-216

DOI: 10.1016/j.ijinfomgt.2017.06.007

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