| アイテムタイプ |
学術雑誌論文 / Journal Article.(1) |
| 公開日 |
2017-07-12 |
| 書誌情報 |
en : Peer-to-Peer Networking and Applications
巻 10,
号 2,
p. 411-420,
発行日 2017-03
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| タイトル |
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|
タイトル |
Finding overlapping communities based on Markov chain and link clustering |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| キーワード |
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|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Community detection |
| キーワード |
|
|
言語 |
en |
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主題Scheme |
Other |
|
主題 |
Random walk |
| キーワード |
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|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Link community |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Overlapping community |
| 資源タイプ |
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|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 著者 |
DENG, Xiaoheng
LI, Genghao
董, 冕雄
太田, 香
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| 室蘭工業大学研究者データベースへのリンク |
|
|
表示名 |
董 冕雄（DONG Mianxiong） |
|
URL |
http://rdsoran.muroran-it.ac.jp/html/100000145_ja.html |
| 室蘭工業大学研究者データベースへのリンク |
|
|
表示名 |
太田 香（OTA Kaoru） |
|
URL |
http://rdsoran.muroran-it.ac.jp/html/100000140_ja.html |
| 抄録 |
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内容記述タイプ |
Abstract |
|
内容記述 |
Since community structure is an important feature of complex network, the study of community detection has attracted more and more attention in recent years. Despite most researchers focus on identifying disjoint communities, communities in many real networks often overlap. In this paper, we proposed a novel MCLC algorithm to discover overlapping communities, which using random walk on the line graph and attraction intensity. Unlike traditional random walk starting from a node, our random walk starts from a link. First we transform an undirected network graph to a weighted line graph, and then random walks on this line graph can be associated with a Markov chain. By calculating the transition probability of the Markov chain, we obtain the similarity between link pairs. Next the links can be clustered into “link communities” by a linkage method, and these nodes between link communities can be overlapping nodes. When converting the “link communities” into the “node communities”, we make a definition of attraction intensity to control the overlapping size. Finally the detected communities are permitted overlapped. Experiments on synthetic networks and some real world networks validate the effectiveness and efficiency of the proposed algorithm. Comparing overlapping modularity Qov with other related algorithms, the results of this algorithm are satisfactory. |
|
言語 |
en |
| 出版者 |
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出版者 |
springer |
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言語 |
en |
| 出版者版へのリンク |
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表示名 |
10.1007/s12083-016-0457-0 |
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URL |
https://doi.org/10.1007/s12083-016-0457-0 |
| DOI |
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|
関連タイプ |
isVersionOf |
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|
識別子タイプ |
DOI |
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|
関連識別子 |
10.1007/s12083-016-0457-0 |
| 日本十進分類法 |
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|
主題Scheme |
NDC |
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主題 |
007 |
| ISSN |
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収録物識別子タイプ |
PISSN |
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収録物識別子 |
1936-6442 |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
1936-6450 |
| 書誌レコードID |
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収録物識別子タイプ |
NCID |
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収録物識別子 |
AA1252589X |
| 権利 |
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|
権利情報 |
The final publication is available at Springer via http://dx.doi.org/10.1007/s12083-016-0457-0 |
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言語 |
en |
| 著者版フラグ |
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出版タイプ |
AM |
|
出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
| フォーマット |
|
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内容記述タイプ |
Other |
|
内容記述 |
application/pdf |
PPNA_10-2_411-420 (887.1 kB)
