Title :
Subtopic Based Topic Evolution Analysis
Author :
Liu, Yan ; Lv, Nan ; Luo, Junyong ; Yang, Huijie
Author_Institution :
Zhengzhou Inst. of Inf. Sci. & Technol., Zhengzhou, China
Abstract :
Traditional topic tracking approaches can obtain the relevant stories. However, the relationship between stories occurred during the topic developing process can not be exhibited clearly. By analyzing the evolution of the topic, the concept subtopic is put forward and the focus of topic evolution analysis is subtopic instead. Four levels topic model is constructed. The subtopic detection algorithm, time slices partition algorithm and topic evolution analysis algorithm are designed. These algorithms make use of the temporal characteristic of topic, partition the news stories into time slices and compute the similarity of these units. As a result, the relationships between the various subtopics in the process of the topic evolution are achieved. Experiments show our algorithms are effective.
Keywords :
text analysis; concept subtopic; subtopic detection algorithm; temporal characteristic; time slices partition algorithm; topic developing process; topic evolution analysis algorithm; topic tracking; Algorithm design and analysis; Clustering algorithms; Data analysis; Data visualization; Detection algorithms; Earthquakes; Information analysis; Information science; Information systems; Partitioning algorithms; subtopic; time slices; topic evolution; topic tracking;
Conference_Titel :
Web Information Systems and Mining, 2009. WISM 2009. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3817-4
DOI :
10.1109/WISM.2009.42