By Topic

Extracting Main Content of a Topic on Online Social Network by Multi-document Summarization

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4 Author(s)
Chunyan Liu ; MOE-MS Key Lab. of Natural Language Process. & Speech, Harbin Inst. of Technol., Harbin, China ; Conghui Zhu ; Tiejun Zhao ; Dequan Zheng

Online social media has become one of the most important ways people communicate, while how to find valuable information from huge amounts of data becomes a key problem. We present a novel topic extraction method that employs topic value of each words and social model attributes as additional features based on the multi-document summarization. The experimental results show that the multi-document summarization with the topic and the sociality are helpful to extract topics from social media.

Published in:

Computational Intelligence and Security (CIS), 2012 Eighth International Conference on

Date of Conference:

17-18 Nov. 2012