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Fuzziness, OWA and linguistic quantifiers for web selection processes

Authors: Ronald R. Yager; Marek Z. Reformat; Giray Gumrah;

Fuzziness, OWA and linguistic quantifiers for web selection processes

Abstract

The Internet becomes an enormous source of information containing billions of documents. Users deal with an overwhelming number of alternatives, and continuously make decisions anytime they want to obtain meaningful information. The paper describes an approach for a simple yet effective selection of the most suitable information that fits user's needs. The novelty of the approach is twofold: the concept of lexicographical-like preferences used for a multi-criteria decision-making with elements of fuzziness and OWA operator; a simple fuzzy number based mechanism for estimating user's degrees of acceptance of criterion satisfaction. The lexicographic preferences allow for mimicking user's attitude that some criteria should be satisfied before other criteria are considered. The acceptance of criterion satisfaction levels are defined with a single threshold that represents a boundary value between acceptable and unacceptable values of attributes of alternatives. The paper includes results of a simple case study preformed on a prototype of a web selection system built using the proposed approach.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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