| Project/Area Number |
20300039
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Media informatics/Database
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| Research Institution | University of Hyogo |
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Principal Investigator |
SUMIYA Kazutoshi University of Hyogo, 環境人間学部, 教授 (60314499)
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| Co-Investigator(Kenkyū-buntansha) |
YUMOTO Takayuki 兵庫県立大学, 工学研究科, 助教 (20453152)
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| Project Period (FY) |
2008 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥18,850,000 (Direct Cost: ¥14,500,000、Indirect Cost: ¥4,350,000)
Fiscal Year 2010: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000)
Fiscal Year 2009: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000)
Fiscal Year 2008: ¥6,890,000 (Direct Cost: ¥5,300,000、Indirect Cost: ¥1,590,000)
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| Keywords | 情報検索 / WWW / コンテンツ統合 / マルチメディア / 情報検索基盤 |
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| Research Abstract |
We developed information retrieval techniques on less-conscious level that is between conscious and unconscious as follows.
(a) Extracting implicit intentions based on user's interactions
(a-1) Extracting user's intentions using media operations: we developed a retrieval method using user's intention that is extracted by media interactions which does not conscious to information retrieval.
(a-2) Modeling and estimating browsing mode from user's browsing behavior: we defined two browsing mode, an exploring mode and a strolling mode in consideration of intensity of user's purpose. Then, we respectively defined two concentration degrees form the aspects of contents and URL domains of browsed pages. We developed a method to estimate user's browsing mode by using the concentration degrees.
(b) A less-conscious information retrieval method using automatic query generation
(b-1) Query generation for retrieving cross media contents: we developed meta-model for spreading user's intentions that is extracted by (a-1) to other media contents' operations as viewing, listening, editing and retrieving. Then, we developed the prototype system and evaluated our method.
(b-2) User assistance method based on user's browsing mode : We developed recommendation technique using social tags for assisting users in a stroll mode defined in (a-2). To find pages to be recommended, we first find combinations of tags, which are in parent-child relationships, from the tags attached to a browsing page. Then we replace a part of these combinations of tags and we find the pages which are similar, generalized or related with the browsing page by using the replaced combination of tags.
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