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ÇѱÛÁ¦¸ñ(Korean Title) |
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¿µ¹®Á¦¸ñ(English Title) |
Graph Classification using Co-occurrent Frequent Subgraphs |
ÀúÀÚ(Author) |
Çѿ뱸
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ÀÌ¿µ±¸
Yongkoo Han
Kisung Park
Young-Koo Lee
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¿ø¹®¼ö·Ïó(Citation) |
VOL 17 NO. 11 PP. 0597 ~ 0601 (2011. 11) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
Frequent subgraphs are widely used as feature vectors in graph classification. It is very important for a graph classification performance to select useful frequent subgraphs from many mined frequent subgraphs. The existing feature selection studies have a shortcoming that is a classification performance degradation from the lack of discrimination power among individual patterns. In this paper, we propose a model based search tree using co-occurrence of frequent subgraphs, and suggest an efficient algorithm. The proposed approach selects more discriminative frequent features considering both discriminative individual and discriminative co- occurrent frequent subgraphs. In experiment, we show that our proposed technique can have a higher graph classification performance compared to existing approach.
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Å°¿öµå(Keyword) |
±×·¡ÇÁ ºÐ·ù
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ºó¹ß ºÎºÐ±×·¡ÇÁ ¸¶ÀÌ´×
Graph Classification
Feature Selection
Frequent Subgraph Mining
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