COSMIC: Conceptually specified multi-instance clusters

Hans Peter Kriegel*, Alexey Pryakhin, Matthias Schubert, Arthur Zimek

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Abstrakt

Recently, more and more applications represent data objects as sets of feature vectors or multi-instance objects. In this paper, we propose COSMIC, a method for deriving concept lattices from multi-instance data based on hierarchical density-based clustering. The found concepts correspond to groups or clusters of multi-instance objects having similar instances in common. We demonstrate that COSMIC outperforms compared methods with respect to efficiency and cluster quality and is capable to extract interesting patterns in multi-instance data sets.

OriginalsprogEngelsk
TitelProceedings - Sixth International Conference on Data Mining, ICDM 2006
ForlagIEEE
Publikationsdatodec. 2006
Sider917-921
ISBN (Trykt)978-0-7695-2701-7
DOI
StatusUdgivet - dec. 2006
Udgivet eksterntJa
Begivenhed6th International Conference on Data Mining, ICDM 2006 - Hong Kong, Kina
Varighed: 18. dec. 200622. dec. 2006

Konference

Konference6th International Conference on Data Mining, ICDM 2006
LandKina
ByHong Kong
Periode18/12/200622/12/2006

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