Title
Rank Factor Granules With Fuzzy Collaborative Clustering And Factor Space Theory
Abstract
This paper makes a discussion on the ranking problem of factor granules where each granule is composed by three parts: the patterns, the factors and the factor- induced information. Hereinto, the factor-induced information refers to the pattern's attributes and the relationship between any two patterns. The overall ranking process is based on the ideology of fuzzy collaborative clustering, by considering a referential factor granule. The collaborative information, i.e. the partition matrices of factor granules, are used to collaborate the clustering for the referential factor granule. These collaborative information are obtained from di r erent sources by di r erent methods. Specially, one kind is obtained from the qualitative data by factor theory-based method. By comparing the difference of the referential factor granule before and after collaboration in aspect of clustering results, we can sort these factor granules: the little the difference, the closer to the top of the sequence.
Year
DOI
Venue
2017
10.1142/S021800141759008X
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
Collaborative information, factor granule, factor space theory, fuzzy collaborative clustering, ranking problem
Ranking,Fuzzy logic,Granule (cell biology),Artificial intelligence,Cluster analysis,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
31
6
0218-0014
Citations 
PageRank 
References 
1
0.37
18
Authors
3
Name
Order
Citations
PageRank
Shihu Liu1293.91
Fusheng Yu263.24
patrick s p wang330347.66