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Hot Topic Detection in Micro-Blog

Author: LiXiaoNing
Tutor: ChenGuang
School: Beijing University of Posts and Telecommunications
Course: Signal and Information Processing
Keywords: micro-blog hot topics extraction WAF modelclustering
CLC: TP393.092
Type: Master's thesis
Year: 2013
Downloads: 77
Quote: 0
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Abstract


The rapid development of the Internet and Communication technology has brought us a lot of new accesses to get information, and one of them is micro-blog. Contribute to its convenience, shortness and timelessness, more and more people begin to use micro-blog. While the mass of the information bring us knowledge, information explosion is caused at the same time. As a result, it is important for people to grasp more information in shorter times, and researches about this have been focused these years.There are many specialties of micro-blog, for example, it is usually very short and the sentences are often free and brief. In addition, there are many useless contents for topic extraction. Because of the reasons mentioned above, traditional methods which are widely used in topic extraction are not suitable for micro-blog. As a result, the work of this article mainly focuses on how to detect hot topics in micro-blog, and the work consists of two parts, one is how to select key words of hot topics, while the other is clustering of the key words to get hot topics. The following experiments prove the effectiveness of the methods we use.In addition, the article introduces two tasks of conference in Natural Language Processing. One is COAE, while the other is TAC. The content is mainly about the definitions of the tasks, the methods we use, and the final results.

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