The Journal of Machine Learning Research
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Evaluating similarity measures: a large-scale study in the orkut social network
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Latent Friend Mining from Blog Data
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Visualization of News Distribution in Blog Space
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)
Learning Social Networks from Web Documents Using Support Vector Classifiers
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Extracting Users' Interests from Web Log Data
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
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With the popularity of Web 2.0 websites, online social networking has thriven rapidly over the last few years. Lots of research attention have been attracted to the large-scale social network extraction and analysis. However, these studies are mostly beneficial to sociologists and researchers in the area of social community studies, but rarely useful to individual users. In this paper, we present a "friends ranking" system - visoLink which is a personal social network analysis service based on user's reading and writing interest. In order to provide a better understanding to user's personal network, a weighted personal social representation and visualization are proposed. Our system prototype shows a much more user friendly design on personal networks than the classical node-edge distance based network visualization.