Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5110720 | International Journal of Information Management | 2018 | 16 Pages |
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
Related Topics
Social Sciences and Humanities
Business, Management and Accounting
Management Information Systems
Authors
Rim Rekik, Ilhem Kallel, Jorge Casillas, Adel M. Alimi,