2012 Fiscal Year Final Research Report
Mining Interesting Substructures based on Various Relevance Measures
Project/Area Number |
23700173
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Intelligent informatics
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Research Institution | Nihon University (2012) Osaka University (2011) |
Principal Investigator |
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Project Period (FY) |
2011 – 2012
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Keywords | データマイニング / 構造データ |
Research Abstract |
In this research, by upgrading hyperclique patterns and conditional contrast patterns in itemset mining into graph domain, we propose correlation and contrast link formation patterns in a dynamic network, respectively. Discovery of sets of link formation patterns having opposite characteristics, i.e., correlation and contrast, can expect to obtain deep understanding of target dataset. Experiments using real world datasets confirm the effectiveness of the proposed framework.
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