講演名 | 2012-08-01 Exploration on Efficient Similar Sentences Extraction , |
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抄録(英) | Semantic similarity measure between sentences is an essential issue for many applications, such as natural language processing, Web page retrieval, question-answer model, and so forth. Although there are a few studies exploring on this issue, most of them focus on how to improve the effectiveness of the problem. In this paper, we address the efficiency issue, i.e., for a given sentence collection, how to efficiently discover the top-k semantic similar sentences to a query. The issue is very important for real applications because the data becomes huge and the existing state-of-the-art strategies cannot satisfy the users' performance requirement. We propose efficient strategies to tackle such problem based on a general framework. Extensive experimental evaluations conducted on two real datasets demonstrate that the efficiency of our proposal outperforms the state-of-the-art approach. |
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キーワード(英) | semantic similarity / query aggregation / top-k |
資料番号 | DE2012-19 |
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研究会情報 | |
研究会 | DE |
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開催期間 | 2012/7/25(から1日開催) |
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講演論文情報詳細 | |
申込み研究会 | Data Engineering (DE) |
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本文の言語 | ENG |
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サブタイトル(和) | |
タイトル(英) | Exploration on Efficient Similar Sentences Extraction |
サブタイトル(和) | |
キーワード(1)(和/英) | / semantic similarity |
第 1 著者 氏名(和/英) | / Yanhui GU |
第 1 著者 所属(和/英) | Institute of Industrial Science, the University of Tokyo |
発表年月日 | 2012-08-01 |
資料番号 | DE2012-19 |
巻番号(vol) | vol.112 |
号番号(no) | 172 |
ページ範囲 | pp.- |
ページ数 | 6 |
発行日 |