Evaluating the information quality of Web sites: A methodology based on fuzzy computing with words: Special Topic Section on Soft Approaches to Information Retrieval and Information Access on the Web

  • Authors:

  • Enrique Herrera-Viedma;Gabriella Pasi;Antonio G. Lopez-Herrera;Carlos Porcel

  • Affiliations:

  • Department of Computer Science and A.I., Library Science Studies School, University of Granada,18071-Granada, Spain;Università degli Studi di Milano Bicocca, Via Bicocca degli Arcimboldi 8, Milano, Italy;Department of Computer Science and A.I., Library Science Studies School, University of Granada,18071-Granada, Spain;Department of Computer Science and A.I., Library Science Studies School, University of Granada,18071-Granada, Spain

  • Venue:
  • Journal of the American Society for Information Science and Technology
  • Year:
  • 2006

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Abstract

An evaluation methodology based on fuzzy computing with words aimed at measuring the information quality of Web sites containing documents is presented. This methodology is qualitative and user oriented because it generates linguistic recommendations on the information quality of the content-based Web sites based on users' perceptions. It is composed of two main components, an evaluation scheme to analyze the information quality of Web sites and a measurement method to generate the linguistic recommendations. The evaluation scheme is based on both technical criteria related to the Web site structure and criteria related to the content of information on the Web sites. It is user driven because the chosen criteria are easily understandable by the users, in such a way that Web visitors can assess them by means of linguistic evaluation judgments. The measurement method is user centered because it generates linguistic recommendations of the Web sites based on the visitors' linguistic evaluation judgments. To combine the linguistic evaluation judgments we introduce two new majority guided linguistic aggregation operators, the Majority guided Linguistic Induced Ordered Weighted Averaging (MLIOWA) and weighted MLIOWA operators, which generate the linguistic recommendations according to the majority of the evaluation judgments provided by different visitors. The use of this methodology could improve tasks such as information filtering and evaluation on the World Wide Web. © 2006 Wiley Periodicals, Inc.