書誌事項
- タイトル別名
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- Maximal Clique Sets with Pseudo Clique Constraints
- ギジ クリーク セイヤク オ モチイタ クリークゾク ノ ゼン レッキョ
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抄録
<p>Many variants of pseudo-cliques have been introduced as a relaxation model of cliques to detect communities in real world networks. For most types of pseudo-cliques, enumeration algorithms can be designed just similar to maximal clique enumerator. However, the problem of enumerating pseudo-cliques is computational hard, because the number of maximal pseudo-cliques-cliques is huge in general. Furthermore, because of the weak requirement of k-plex, sparse communities are also allowed depending on the parameter k. To obtain a class of more dense pseudo cliques and to improve the computational performance, we introdue a derived graph whose vertices are cliques in the original input graph. Then our target pseudo must be a clique or a pseudo clique of the derived graph under an additional constraint requiring density in the original graph. An enumerator for this new class is designed and its computational efficientcy is experimentally verfied.</p>
収録刊行物
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- 人工知能学会研究会資料 人工知能基本問題研究会
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人工知能学会研究会資料 人工知能基本問題研究会 96 (0), 10-, 2015-01-07
一般社団法人 人工知能学会
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詳細情報 詳細情報について
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- CRID
- 1390007072283693440
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- NII論文ID
- 40020323207
- 130008061494
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- NII書誌ID
- AA11977943
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- ISSN
- 24364584
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- NDL書誌ID
- 026026785
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用可