Abstract: Chinese online encyclopedia carries a huge amount of high quality information.Previous studies have utilized it for different knowledge acquisition tasks.For instance,the articles with similar subjects are grouped together into ca-tegories.Constructing a certain category topical hierarchy from the online encyclopedia is significantly beneficial for many applications such as search and browsing,information organizing and information retrieval.However,no attempts have been made to explore topic hierarchy of given category in online encyclopedia.Considering most of the online encyclopedia is heterogeneous and rough,this paper proposed a novel scheme of constructing topic hierarchy based on the Bayesian network.This scheme will incorporate both the structured contents table and unstructured text descriptions in the articles of the same category into automatic topic hierarchy learning for the online encyclopedia category using the algorithm of maximum spanning tree on the Bayesian topic network.Experimental results show that,compared with the existed encyclopedia topical hierarchy,our approach expand the content of 4 times while maintaining the accuracy of 75%.

Key words: Chinese online encyclopedia,Topic hierarchy,Structured contents table,Unstructured text description