Review of bisoNet abstraction techniques

Fang Zhou; Sébastien Mahler; Hannu Toivonen

doi:10.1007/978-3-642-31830-6_12

Review of bisoNet abstraction techniques

Fang Zhou^*
, Sébastien Mahler
, Hannu Toivonen

^*此作品的通讯作者

Helsinki Institute for Information Technology

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

8 引用（Scopus）

摘要

BisoNets represent relations of information items as networks. The goal of BisoNet abstraction is to transform a large BisoNet into a smaller one which is simpler and easier to use, although some information may be lost in the abstraction process. An abstracted BisoNet can help users to see the structure of a large BisoNet, or understand connections between distant nodes, or discover hidden knowledge. In this paper we review different approaches and techniques to abstract a large BisoNet. We classify the approaches into two groups: preference-free methods and preference-dependent methods.

源语言	英语
主期刊名	Bisociative Knowledge Discovery
主期刊副标题	An Introduction to Concept, Algorithms, Tools, and Applications
编辑	Michael R. Berthold
页	166-178
页数	13
DOI	https://doi.org/10.1007/978-3-642-31830-6_12
出版状态	已出版 - 2012
已对外发布	是

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	7250
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

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10.1007/978-3-642-31830-6_12

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引用此

Zhou, F., Mahler, S., & Toivonen, H. (2012). Review of bisoNet abstraction techniques. 在 M. R. Berthold (编辑), Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications (页码 166-178). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 7250). https://doi.org/10.1007/978-3-642-31830-6_12

Zhou, Fang ; Mahler, Sébastien ; Toivonen, Hannu. / Review of bisoNet abstraction techniques. Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications. 编辑 / Michael R. Berthold. 2012. 页码 166-178 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "BisoNets represent relations of information items as networks. The goal of BisoNet abstraction is to transform a large BisoNet into a smaller one which is simpler and easier to use, although some information may be lost in the abstraction process. An abstracted BisoNet can help users to see the structure of a large BisoNet, or understand connections between distant nodes, or discover hidden knowledge. In this paper we review different approaches and techniques to abstract a large BisoNet. We classify the approaches into two groups: preference-free methods and preference-dependent methods.",

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Zhou, F, Mahler, S & Toivonen, H 2012, Review of bisoNet abstraction techniques. 在 MR Berthold (编辑), Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 7250, 页码 166-178. https://doi.org/10.1007/978-3-642-31830-6_12

Review of bisoNet abstraction techniques. / Zhou, Fang; Mahler, Sébastien; Toivonen, Hannu.
Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications. 编辑 / Michael R. Berthold. 2012. 页码 166-178 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 7250).

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

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AU - Mahler, Sébastien

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N2 - BisoNets represent relations of information items as networks. The goal of BisoNet abstraction is to transform a large BisoNet into a smaller one which is simpler and easier to use, although some information may be lost in the abstraction process. An abstracted BisoNet can help users to see the structure of a large BisoNet, or understand connections between distant nodes, or discover hidden knowledge. In this paper we review different approaches and techniques to abstract a large BisoNet. We classify the approaches into two groups: preference-free methods and preference-dependent methods.

AB - BisoNets represent relations of information items as networks. The goal of BisoNet abstraction is to transform a large BisoNet into a smaller one which is simpler and easier to use, although some information may be lost in the abstraction process. An abstracted BisoNet can help users to see the structure of a large BisoNet, or understand connections between distant nodes, or discover hidden knowledge. In this paper we review different approaches and techniques to abstract a large BisoNet. We classify the approaches into two groups: preference-free methods and preference-dependent methods.

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DO - 10.1007/978-3-642-31830-6_12

M3 - 章节

AN - SCOPUS:84864120322

SN - 9783642318290

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BT - Bisociative Knowledge Discovery

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ER -

Zhou F, Mahler S, Toivonen H. Review of bisoNet abstraction techniques. 在 Berthold MR, 编辑, Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications. 2012. 页码 166-178. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-31830-6_12

Review of bisoNet abstraction techniques

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