Title :
An adaptive topic tracking method based on feedback stories
Author :
Yan Zheng ; Ran Lu
Author_Institution :
Shandong Normal Univ., Jinan, China
Abstract :
In topic tracking, topic model influences the accurate of topic tracking, and the features of topic tracking that initial topic related stories are few and topic evolutes dynamically, lead to initial topic model could not express a topic accurately. So, in this paper, we proposed an adaptive topic tracking method based on feedback stories, amend topic model dynamically by feedback stories, which collected through dynamic threshold, and increase the weight of named entity to express a topic better. Experimental results indicate that, this method could solve the topic shifting problem effectively, and the miss tracking rate and fault tracking rate decreased a lot in topic tracking.
Keywords :
feedback; information retrieval; adaptive topic tracking method; dynamic threshold; fault tracking rate; feedback stories; information retrieval; miss tracking rate; named entity; topic model; topic shifting problem; Adaptation models; Computational modeling; Silicon; dynamic threshold; feedback stories; named entity; topic model; topic tracking;
Conference_Titel :
Information Technology in Medicine and Education (ITME), 2012 International Symposium on
Conference_Location :
Hokodate, Hokkaido
Print_ISBN :
978-1-4673-2109-9
DOI :
10.1109/ITiME.2012.6291475