Natural document clustering by clique percolation in random graphs
Document clustering techniques mostly depend on models that impose explicit and/or implicit priori assumptions as to the number, size, disjunction characteristics of clusters, and/or the probability distribution of clustered data. As a result, the clustering effects tend to be unnatural and stray aw...
Saved in:
Main Authors: | GAO, Wei, WONG, Kam-Fai |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2006
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/4603 https://ink.library.smu.edu.sg/context/sis_research/article/5606/viewcontent/Gao_Wong2006_Chapter_NaturalDocumentClusteringByCli.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Clique percolation for finding naturally cohesive and overlapping document clusters
by: GAO, Wei, et al.
Published: (2006) -
Social media content analysis: Natural language processing and beyond
by: WONG, Kam-Fai, et al.
Published: (2017) -
Clique coverings and clique partitions of the K-power of graphs
by: Tanawat Wichianpaisarn
Published: (2014) -
Gibberish, assistant, or master? Using tweets linking to news for extractive single-document summarization
by: WEI, Zhongyu, et al.
Published: (2015) -
A link-bridged topic model for cross-domain document classification
by: YANG, Pei, et al.
Published: (2013)