Improved Bidirectional CABOSFV Based on Multi-Adjustment Clustering and Simulated Annealing

Improved Bidirectional CABOSFV Based on Multi-Adjustment Clustering and Simulated Annealing

Although Clustering Algorithm Based on Sparse Feature Vector (CABOSFV) and its related algorithms are efficient for high dimensional sparse data clustering, there exist several imperfections. Such imperfections as subjective parameter designation and order sensibility of clustering process would eve...

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Bibliographic Details
Main Authors: Yang Minghan, Gao Xuedong, Li Ling
Format: Article
Language:English
Published: Sciendo 2016-12-01
Series:Cybernetics and Information Technologies
Subjects:
data mining
high dimensional sparse data
simulated annealing
clustering validity
Online Access:https://doi.org/10.1515/cait-2016-0075

Internet

https://doi.org/10.1515/cait-2016-0075

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