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Fuzzy multisets and fuzzy clustering of documents

Authors: Sadaaki Miyamoto;

Fuzzy multisets and fuzzy clustering of documents

Abstract

Aims at developing a method of fuzzy clustering based on fuzzy multisets. Data clustering has been discussed in relation to information retrieval models and fuzzy multisets provide an appropriate model of information retrieval on the WWW. Fuzzy clustering of fuzzy multisets is thus necessary for application to an information retrieval model. A term-document matrix in which entries are multisets are considered. Two dissimilarity measures on fuzzy multisets are proposed. Two methods of fuzzy c-means using these measures are studied in which calculation of cluster centers is focused upon.

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    influence
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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!
9
Average
Top 10%
Average
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