A Link-Based Rank of Postings in Newsgroup

Authors:
Hongbo Liu;Jiahai Yang;Jiaxin Wang;Yu Zhang
Affiliations:
The Network Research Center,;The Network Research Center,;Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China;Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China
Venue:
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Year:
2007

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Abstract

Discussion systems such as Usenet, BBS, Forum are important resources for information sharing, view exchanging, problem solving and product feedback, etc. on Internet. The postings in newsgroups on Usenet represents the judgments and choices of participators. The structure of postings could provide helpful information for the users. In this paper, we present a method called PostRank to rank the postings based on the structure of newsgroup. Its results correspond to the eigenvectors of the transition probability matrix and the stationary vectors of the Markov chains. It could provide useful global information for the newsgroup and it can be used to help the users access information in it more effectively and efficiently. This method can be also applied on other discussion systems. Some experimental results and discussions on real data sets collected by us are also provided.