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Procedia Computer Science
Article . 2016 . Peer-reviewed
License: CC BY NC ND
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Procedia Computer Science
Article
License: CC BY NC ND
Data sources: UnpayWall
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Procedia Computer Science
Article . 2016
License: CC BY NC ND
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Multi-criteria Web Mining with DRSA

Authors: Couto, Ayrton Benedito Gaia do; Gomes, Luiz Flavio Autran Monteiro;

Multi-criteria Web Mining with DRSA

Abstract

AbstractThis study demonstrates the application of the Dominance principle to a particular case of web (World Wide Web) content search under Multi-criteria approach: searching for “Rio de Janeiro” (City and/or State, in Brazil) followed by other attributes (or criteria). It is known that depending on the content of research that is carried out through a “seeker” (“search engine”) on the Internet, the result may fall short of the desirable, in terms of quantity and quality of the sites returned. The Dominance principle, subsequent to treatment of the collected information (unstructured data) on the Internet, aimed at revealing patterns (or logical rules) on a set of information and showed how a web content search can become more effective at a significant universe of information. Other techniques and tools have been applied to mining content on the Web, and as shown in this study. The choice of the Dominance principle associated to Rough Set Theory as Multi-criteria decision technique is due to the possibility of inaccurate data (inconsistent) and the need for treatment of these inaccuracies when processing an information system (data table) under a mathematical perspective, and do not need a history of these data. The use of Rough Set Theory and the Dominance principle associated with the probabilistic relationship between conditions and decisions in decision algorithms, is showed by the possibility of there being uncertain data to yield an essential set of effectively consistent information.

Keywords

Rough set theory, Multi-criteria analysis, Web mining ;, Dominance principle

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
6
Average
Average
Average
gold