Unsupervised cross-domain learning by interaction information co-clustering

Shin Ando, Einoshin Suzuki

研究成果: 著書/レポートタイプへの貢献会議での発言

4 引用 (Scopus)

抄録

In real-world data mining applications, one often has access to multiple datasets that are relevant to the task at hand. However, learning from such datasets can be difficult as they are often drawn from different domains, i.e., not identically distributed or differ in class or feature sets. In this paper, we consider the problem of learning the class structures of related domains in an unsupervised manner. Its setting generalizes that of information filtering and novelty detection applications which addresses both known and unknown classes. We propose a co-clustering framework for estimating and adapting the class structures of two related domains, enabling the analyses of shared and unique classes. We define an objective function using interaction information to take account of the divergence between the corresponding clusters of respective domains. We present an iterative algorithm which alternates object and feature clustering and converges to a local minimum of the objective function. We present empirical results using text benchmarks, comparing the proposed algorithm and combinations of conventional approaches in problems of partitioning documents and detecting unknown topics.

元の言語英語
ホスト出版物のタイトルProceedings - 8th IEEE International Conference on Data Mining, ICDM 2008
ページ13-22
ページ数10
DOI
出版物ステータス出版済み - 12 1 2008
イベント8th IEEE International Conference on Data Mining, ICDM 2008 - Pisa, イタリア
継続期間: 12 15 200812 19 2008

出版物シリーズ

名前Proceedings - IEEE International Conference on Data Mining, ICDM
ISSN(印刷物)1550-4786

その他

その他8th IEEE International Conference on Data Mining, ICDM 2008
イタリア
Pisa
期間12/15/0812/19/08

Fingerprint

Information filtering
Data mining

All Science Journal Classification (ASJC) codes

  • Engineering(all)

これを引用

Ando, S., & Suzuki, E. (2008). Unsupervised cross-domain learning by interaction information co-clustering. : Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008 (pp. 13-22). [4781096] (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDM.2008.92

Unsupervised cross-domain learning by interaction information co-clustering. / Ando, Shin; Suzuki, Einoshin.

Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008. 2008. p. 13-22 4781096 (Proceedings - IEEE International Conference on Data Mining, ICDM).

研究成果: 著書/レポートタイプへの貢献会議での発言

Ando, S & Suzuki, E 2008, Unsupervised cross-domain learning by interaction information co-clustering. : Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008., 4781096, Proceedings - IEEE International Conference on Data Mining, ICDM, pp. 13-22, 8th IEEE International Conference on Data Mining, ICDM 2008, Pisa, イタリア, 12/15/08. https://doi.org/10.1109/ICDM.2008.92
Ando S, Suzuki E. Unsupervised cross-domain learning by interaction information co-clustering. : Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008. 2008. p. 13-22. 4781096. (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDM.2008.92
Ando, Shin ; Suzuki, Einoshin. / Unsupervised cross-domain learning by interaction information co-clustering. Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008. 2008. pp. 13-22 (Proceedings - IEEE International Conference on Data Mining, ICDM).
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