2010 Fiscal Year Final Research Report
Data mining from large multimedia contents and its applications
| Project/Area Number |
20500140
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Hiroshima City University |
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Principal Investigator |
UCHIDA Tomoyuki Hiroshima City University, 情報科学研究科, 准教授 (70264934)
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| Co-Investigator(Kenkyū-buntansha) |
SHOUDAI Takayoshi 九州大学, システム情報科学研究院, 准教授 (50226304)
MIYAHARA Tetsuhiro 広島市立大学, 情報科学研究科, 准教授 (90209932)
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| Co-Investigator(Renkei-kenkyūsha) |
ITOKAWA Yuko 広島国際大学, 心理科学部, 助教 (40341234)
SUZUKI Yusuke 広島市立大学, 情報科学研究科, 助教 (10398464)
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| Project Period (FY) |
2008 – 2010
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| Keywords | グラフアルゴリズム / 機械学習 / データマイニング / 情報検索システム |
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| Research Abstract |
We proposed graph mining techniques for extracting all correlations of different kinds of attributes (e.g., keywords, objects in images, and graph structures) from large amounts of contents including multimedia. We formally defined a tree pattern, which can represent characteristics such as the usage of keywords (e.g., words, objects in image, and the structural relations among nodes in which characteristic words appear) in multimedia contents. Based on computational machine learning, we proposed efficient pattern matching algorithms and efficient graph mining algorithms for tree patterns and graph patterns. Moreover, in order to construct a theoretical base of user-oriented information retrieval system for multimedia contents, we proposed efficient methods of managing all extracted tree patterns.
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