http://scholars.ntou.edu.tw/handle/123456789/23181
標題: | Improving annotation categorization performance through integrated social annotation computation | 作者: | Su, Addison Y. S. Yang, Stephen J. H. |
關鍵字: | TEXT CATEGORIZATION | 公開日期: | 1-十二月-2010 | 出版社: | PERGAMON-ELSEVIER SCIENCE LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND | 卷: | 37 | 期: | 12 | 起(迄)頁: | 8736-8744 | 來源出版物: | Expert Systems with Applications (SCI) | 摘要: | People can identify and organize their ideas and comments with respect to relevant concept topics through using annotation systems. Those annotation systems are obvious that only supports a simple and manual categorization approach. The manual approach is a difficult and time-consuming task for general annotators. Therefore, we propose a requirement annotation categorization which helps annotators to promote the manual annotation categorization effectiveness. Moreover, we propose an integrated social annotation computation which improves the performance of our annotation categorization. In summary, the proposed annotation categorization is verified through experiments using real users' data sets. We achieved the 83.11% average accuracy for the proposed annotation categorization with integrated social annotation computation. We also show that the proposed annotation categorization requires only 17-20% average processing time (in comparison with the manual approach) is efficient. (C) 2010 Elsevier Ltd. All rights reserved. |
URI: | http://scholars.ntou.edu.tw/handle/123456789/23181 | ISSN: | 0957-4174 | DOI: | 10.1016/j.eswa.2010.06.041 |
顯示於: | 資訊工程學系 |
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