Dynamic topic detection and tracking based on knowledge base
|Dynamic topic detection and tracking based on knowledge base|
|Author(s)||Wang S., Du J., Liang M., Chen L.|
|Published in||Proceedings - 2010 3rd IEEE International Conference on Broadband Network and Multimedia Technology, IC-BNMT2010|
|Keyword(s)||Knowledge base, Topic detection, Topic tracking, Topic update (Extra: Dynamic threshold, Initial information, Knowledge base, Similarity measurements, Time distance, Time line, Topic detection, Topic detection and tracking, Topic model, Topic tracking, Topic update, Wikipedia, Broadband networks, Information analysis, Information retrieval systems, Knowledge based systems)|
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Dynamic topic detection and tracking based on knowledge base is a 2010 conference paper written in English by Wang S., Du J., Liang M., Chen L. and published in Proceedings - 2010 3rd IEEE International Conference on Broadband Network and Multimedia Technology, IC-BNMT2010.
In order to solve the sparse initial information problem when the topic model was established ever before, this paper establishes the Wikipedia based news event knowledge base. Referring to this knowledge base, we calculate the weight of the news model, make the similarity measurement based on the time distance, make the clustering based on time line, and apply the dynamic threshold strategy to detect and track the topics automatically in the news materials. The experiment result verifies the validity of this method.
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