The density-based agglomerative information bottleneck

Ren, Yongli, Ye, Yangdong and Li, Gang 2008, The density-based agglomerative information bottleneck, Lecture notes in computer science, vol. 5351, pp. 333-344, doi: 10.1007/978-3-540-89197-0_32.

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Title The density-based agglomerative information bottleneck
Author(s) Ren, Yongli
Ye, Yangdong
Li, GangORCID iD for Li, Gang
Journal name Lecture notes in computer science
Volume number 5351
Start page 333
End page 344
Total pages 12
Publisher Springer
Place of publication Berlin, Germany
Publication date 2008
ISSN 0302-9743
Keyword(s) information bottleneck
hierarchical tree-structure
Summary The Information Bottleneck method aims to extract a compact representation which preserves the maximum relevant information. The sub-optimality in agglomerative Information Bottleneck (aIB) algorithm restricts the applications of Information Bottleneck method. In this paper, the concept of density-based chains is adopted to evaluate the information loss among the neighbors of an element, rather than the information loss between pairs of elements. The DaIB algorithm is then presented to alleviate the sub-optimality problem in aIB while simultaneously keeping the useful hierarchical clustering tree-structure. The experiment results on the benchmark data sets show that the DaIB algorithm can get more relevant information and higher precision than aIB algorithm, and the paired t-test indicates that these improvements are statistically significant.
Language eng
DOI 10.1007/978-3-540-89197-0_32
Field of Research 080107 Natural Language Processing
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2008, Springer-Verlag Berlin Heidelberg
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Document type: Journal Article
Collection: School of Information Technology
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