BBS topic tracking method for military public opinion based on Wikipedia
Liu Xiao-liang · Journal of Computer Applications · 2012
A method using Wikipedia as semantic and background knowledge was proposed for public military topic tracking on BBS.The semantic profiles of a post was modeled by text graph,in which nodes and edges were considered as: Wikipedia-based words semantic relevance,word co-occurrence with military themes and post structure,then a modified link mining method was utilized to extract the key words from text graph.At last,topic tracking was realized by calculating the semantic relevance of keywords between the post and topic.In the experiment,the results show that this method can effectively solve the problem of semantic feature scarcity in BBS-oriented military topic tracking.