Inferring Web communities from link topology
Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems
Web-collaborative filtering: recommending music by crawling the Web
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Creating a Web community chart for navigating related communities
Proceedings of the 12th ACM conference on Hypertext and Hypermedia
Applying data mining in investigating money laundering crimes
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
An article language model for BBS search
ICWE'05 Proceedings of the 5th international conference on Web Engineering
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Bulletin board system (BBS) is popular on the Internet. This paper attempts to identify communities of interest-sharing users on BBS. First, the paper formulates a general model for the BBS data, consisting of a collection of user IDs described by two views to their behavior actions along the timeline, i.e., the topics of the posted messages and the boards to which the messages are posted. Based on this model which contains no explicit link information between users, a uni-party data community generation algorithm called ISGI is proposed, which employs a specifically designed hierarchical similarity function to measure the correlations between two different individual users. Then, the BPUC algorithm is proposed, which uses the generated communities to predict users' behavior actions under certain conditions for situation awareness or personalized services development. For instance, the BPUC predictions may be used to answer questions such as "what will be the likely behavior user X may take if he/she logs into the BBS tomorrow?". Experiments on a large scale, real-world BBS data set demonstrate the effectiveness of the proposed model and algorithms.