Extraction of Similar Words Based on Time-correlation and Co-occurrence Probability from Tweets of the Same Topic
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- Hisano Yuichiro
- University of Tsukuba
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- Sawase Kazuhito
- University of Tsukuba
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- Nobuhara Hajime
- University of Tsukuba
Bibliographic Information
- Other Title
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- 同一ハッシュタグツイート群における時空間相関情報に基づく単語類似度の計量
- ドウイツ ハッシュタグツイートグン ニ オケル ジクウカン ソウカン ジョウホウ ニ モトズク タンゴ ルイジド ノ ケイリョウ
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Abstract
In order to reduce various onomastic expressions for efficient tweet topic retrieval/clustering, a construction method of twitter dictionaries based on tweets extraction and their time-correlation is proposed. In the proposed method, similarities between keywords are calculated by the time-correlation of each word and co-occurrence probability. Furthermore, the proposed method divides the target time line to reduce the computational cost of twitter dictionaries construction. Through experiments with 101,714 tweets with the hashtags related to ``NHK kohaku-utagassen'', the effectiveness of the proposed division method compared with the method calculated using entire time line region is confirmed.
Journal
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- Proceedings of the Fuzzy System Symposium
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Proceedings of the Fuzzy System Symposium 28 (0), 394-397, 2012
Japan Society for Fuzzy Theory and Intelligent Informatics
- Tweet
Details 詳細情報について
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- CRID
- 1390282680650369152
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- NII Article ID
- 130005456159
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- NII Book ID
- AA12165648
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- ISSN
- 18820212
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- NDL BIB ID
- 023989447
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed