Mining the interests of Chinese microbloggers via keyword extraction
Mining the interests of Chinese microbloggers via keyword extraction
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DOI：
10.1007/s11704-011-1174-8
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发表时间：
2012-01
影响因子：
4.2
通讯作者：
Zhiyuan Liu;Xinxiong Chen;Maosong Sun
中科院分区：
文献类型：
--
作者：
Zhiyuan Liu;Xinxiong Chen;Maosong Sun
微博为网络用户之间的信息交流和分享提供了一个新的平台。用户可以通过微博表达意见，记录日常生活。用户发布的微博在某种程度上表明了他们的兴趣。我们的目标是通过从微博中提取关键词来挖掘用户兴趣。传统的关键词提取方法通常是为正式文档设计的，如新闻文章或科学论文。然而，微博用户发布的消息通常噪音很大，充满了新词，这给关键词提取带来了挑战。在本文中，我们将基于翻译的方法和基于频率的方法结合起来进行关键词提取。在我们的实验中，我们从中国最大的微博网站--新浪微博中提取了微博用户的关键词。实验结果表明，该方法能够准确、高效地识别用户兴趣。
Microblogging provides a new platform for communicating and sharing information among Web users. Users can express opinions and record daily life using microblogs. Microblogs that are posted by users indicate their interests to some extent. We aim to mine user interests via keyword extraction from microblogs. Traditional keyword extraction methods are usually designed for formal documents such as news articles or scientific papers. Messages posted by microblogging users, however, are usually noisy and full of new words, which is a challenge for keyword extraction. In this paper, we combine a translation-based method with a frequency-based method for keyword extraction. In our experiments, we extract keywords for microblog users from the largest microblogging website in China, Sina Weibo. The results show that our method can identify users’ interests accurately and efficiently.