Generating social network features for link-based classification

Jun Karamon, Yutaka Matsuo, Hikaru Yamamoto, Mitsuru Ishizuka

研究成果: Conference contribution

9 被引用数 (Scopus)

抄録

There have been numerous attempts at the aggregation of attributes for relational data mining. Recently, an increasing number of studies have been undertaken to process social network data, partly because of the fact that so much social network data has become available. Among the various tasks in link mining, a popular task is link-based classification, by which samples are classified using the relations or links that are present among them. On the other hand, we sometimes employ traditional analytical methods in the field of social network analysis using e.g., centrality measures, structural holes, and network clustering. Through this study, we seek to bridge the gap between the aggregated features from the network data and traditional indices used in social network analysis. The notable feature of our algorithm is the ability to invent several indices that are well studied in sociology. We first define general operators that are applicable to an adjacent network. Then the combinations of the operators generate new features, some of which correspond to traditional indices, and others which are considered to be new. We apply our method for classification to two different datasets, thereby demonstrating the effectiveness of our approach.

本文言語English
ホスト出版物のタイトルKnowledge Discovery in Database
ホスト出版物のサブタイトルPKDD 2007 - 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Proceedings
出版社Springer Verlag
ページ127-139
ページ数13
ISBN(印刷版)9783540749752
DOI
出版ステータスPublished - 2007
外部発表はい
イベント11th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2007 - Warsaw, Poland
継続期間: 2007 9 172007 9 21

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4702 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other11th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2007
CountryPoland
CityWarsaw
Period07/9/1707/9/21

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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