Evaluating the informative quality of web sites by fuzzy computing with words

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Abstract

In this paper we present a method based on fuzzy computing with words to measure the informative quality of Web sites used to publish information stored in XML documents. This method generates linguistic recommendations on the informative quality of Web sites. This method is made up of both an evaluation scheme to analyze the informative quality of such Web sites and a generation method of linguistic recommendations. The evaluation scheme presents both technical criteria of Web site design and criteria related to the content of information of Web sites. It is oriented to the user because the chosen criteria are user friendly, in such a way that visitors to a Web site can assess them by means of linguistic evaluation judgements. The generation method generates linguistic recommendations of Web sites based on those linguistic evaluation judgements using the LOWA and LWA operators. Then, when a user looks for information on the Web we can help him/her with both recommendations on Web sites which store the retrieved documents and also recommendations on other Web sites which store other documents of interest related to his/her information needs. With this proposal information filtering and evaluation possibilities on the Web are increased.

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APA

Herrera-Viedma, E., Peis, E., Olvera, M. D., Herrera, J. C., & Montero, Y. H. (2003). Evaluating the informative quality of web sites by fuzzy computing with words. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2663, pp. 62–72). Springer Verlag. https://doi.org/10.1007/3-540-44831-4_8

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