Optimizing Academic Conference Classification Using Social Tags

Jing Xia, Kunmei Wen, Ruixuan Li, X. Gu
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引用次数: 12

Abstract

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.
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利用社会标签优化学术会议分类
将学术会议自动分类为语义主题,可以改善用户的学术搜索和浏览。社会标签是描述学术会议主题的一种日益流行的方式。然而,利用社会标签进行学术会议分类的研究尚未得到重视。基于这一观察,本文提出了一种结合社会标签和学术会议内容的方法来改进自动识别学术会议分类。该方法采用不同的自动分类算法,利用社会标签来提高分类质量。实验结果表明,该方法优于仅利用内容对学术会议进行分类的方法,精度测度分数提高1%,F1测度分数提高1.64%,证明了该方法的有效性。
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