Characterizing browsing strategies in the World-Wide Web
Proceedings of the Third International World-Wide Web conference on Technology, tools and applications
Matrix computations (3rd ed.)
Net gain: expanding markets through virtual communities
Net gain: expanding markets through virtual communities
ACM Computing Surveys (CSUR)
Document Categorization and Query Generation on the World Wide WebUsing WebACE
Artificial Intelligence Review - Special issue on data mining on the Internet
Principles of data mining
Principal Direction Divisive Partitioning
Data Mining and Knowledge Discovery
Linux Apache Web Server Administration (Craig Hunt Linux Library Series)
Linux Apache Web Server Administration (Craig Hunt Linux Library Series)
Analysis of navigation behaviour in web sites integrating multiple information systems
The VLDB Journal — The International Journal on Very Large Data Bases
A comparative analysis on the bisecting K-means and the PDDP clustering algorithms
Intelligent Data Analysis
Ethical aspects of web log data mining
International Journal of Information Technology and Management
An unsupervised clustering approach for leukaemia classification based on DNA micro-arrays data
Intelligent Data Analysis
A dissimilarity measure for automate moderation in online social networks
Proceedings of the 4th International Workshop on Web Intelligence & Communities
A new dissimilarity measure for online social networks moderation
Web Intelligence and Agent Systems - Web Intelligence and Communities
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In this paper the analysis and Data-Mining of a large data-set related to a very popular Italian Virtual Community is presented. The Community is constituted by more than half-million registered users, each characterized by a unique nickname and a personal "profile" filled during a registration procedure, on a voluntary basis. Two data-sets have been considered: the Data-Base of the Users (nicknames and profiles), and the log-file of the server hosting the Community web-site. This work is constituted by three main parts: 1) analysis and clustering of the User Data-Base; 2) sessionization of the log-file and clustering of the navigation session database; 3) correlation of User clusters and navigation session clusters. This analysis provides a complete and full-rounded picture of the Virtual Community.