2013 Fiscal Year Final Research Report
Speeding up the similarity search by contractive embedding methods
| Project/Area Number |
23500128
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Media informatics/Database
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| Research Institution | University of Shizuoka |
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Principal Investigator |
IKEDA Tetsuo 静岡県立大学, 経営情報学部, 教授 (60363727)
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| Co-Investigator(Kenkyū-buntansha) |
SAITO Kazumi 静岡県立大学, 経営情報部, 教授 (80379544)
MUTOH Nobuaki 静岡県立大学, 経営情報部, 准教授 (40275102)
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| Project Period (FY) |
2011 – 2013
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| Keywords | 情報検索 / 類似検索 |
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| Research Abstract |
The purpose of our research is to develop efficient similarity search methods of multimedia data such as picture images and movies. Although Bustos and others have devised several pivot-based methods and have obtained the excellent results, in this field there is still room for further investigation.
We devised two pivot-based similarity search methods. The first method is characterized by improving Bustos's exchange algorithm of pivot set elements. The second method is a generalized pivot method based on Manhattan Distance. We devised it by extending one of our previously-developed methods. By experiments, we showed that both methods were better than the conventional methods in retrieval performance and creation time of pivot sets.
Furthermore, we devised extraction methods of the communities in networks and network visualization methods in order to make clarifying the nature of the multimedia data more efficient.
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