Optimizing Academic Conference Classification using Social Tags
出版社：
- 会议名称：The 13th International Conference on Computational Science and Engineering (CSE 2010)
- 举办地点：Hong Kong,China
- 举办日期：December 11-13,2010
- 页数：289-294
摘要内容：
Automatically classifying academic conference into semantic topic promises improved academic search and browsing for users. Social tagging is an increasingly popular way of describing the topic of academic conference. However, no attention has been devoted to academic conference classification by making use of social tags. Motivated by this observation, this paper proposes a method which utilizes social tags as well as the content of academic conference in order to improve automatically identifying academic conference classification. The proposed method applies different automatic classification algorithms to improve classification quality by using social tags. Experimental results show that this method mentioned above performs better than the method which only utilizes the content to classify academic conference with 1% Precision measure score increase and 1.64% F1 measure score increase, which demonstrates the effectiveness of the proposed method.
关键词：
- classification；academic conference；feature selection
