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

^*Corresponding author for this work

Helsinki Institute for Information Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

8 Scopus citations

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.

Original language	English
Title of host publication	Bisociative Knowledge Discovery
Subtitle of host publication	An Introduction to Concept, Algorithms, Tools, and Applications
Editors	Michael R. Berthold
Pages	166-178
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-642-31830-6_12
State	Published - 2012
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7250
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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

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Zhou, F., Mahler, S., & Toivonen, H. (2012). Review of bisoNet abstraction techniques. In M. R. Berthold (Ed.), Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications (pp. 166-178). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 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. editor / Michael R. Berthold. 2012. pp. 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.",

author = "Fang Zhou and S{\'e}bastien Mahler and Hannu Toivonen",

year = "2012",

doi = "10.1007/978-3-642-31830-6\_12",

language = "英语",

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Zhou, F, Mahler, S & Toivonen, H 2012, Review of bisoNet abstraction techniques. in MR Berthold (ed.), 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), vol. 7250, pp. 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. ed. / Michael R. Berthold. 2012. p. 166-178 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7250).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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T1 - Review of bisoNet abstraction techniques

AU - Zhou, Fang

AU - Mahler, Sébastien

AU - Toivonen, Hannu

PY - 2012

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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

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 166

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BT - Bisociative Knowledge Discovery

A2 - Berthold, Michael R.

ER -

Zhou F, Mahler S, Toivonen H. Review of bisoNet abstraction techniques. In Berthold MR, editor, Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications. 2012. p. 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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