Effective latent space graph-based re-ranking model with global consistency
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Direct Zero-Norm Optimization for Feature Selection
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Semi-supervised Learning from General Unlabeled Data
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
A generalized Co-HITS algorithm and its application to bipartite graphs
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning to recommend with social trust ensemble
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Entropy-biased models for query representation on the click graph
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
A Survey of Human Computation Systems
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Learning to recommend with trust and distrust relationships
Proceedings of the third ACM conference on Recommender systems
Proceedings of the 18th ACM conference on Information and knowledge management
A social recommendation framework based on multi-scale continuous conditional random fields
Proceedings of the 18th ACM conference on Information and knowledge management
MatchSim: a novel neighbor-based similarity measure with maximum neighborhood matching
Proceedings of the 18th ACM conference on Information and knowledge management
Enhancing expertise retrieval using community-aware strategies
Proceedings of the 18th ACM conference on Information and knowledge management
Automobile, car and BMW: horizontal and hierarchical approach in social tagging systems
Proceedings of the 2nd ACM workshop on Social web search and mining
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With the advent of Web 2.0, Social Computing has emerged as one of the hot research topics recently. Social Computing involves the collecting, extracting, accessing, processing, computing, visualizing, etc. of social signals and information. More specifically, this tutorial places special emphases in machine learning, data mining, information retrieval, and other computational techniques involved in collective intelligence processing of social behavior data collected from blogs, wikis, clickthrough data, query logs, tags, etc., and from areas such as social networks, social search, social media, social bookmarks, social news, social knowledge sharing, and social games. In this tutorial, I plan to give an introduction to Social Computing and elaborate on how the various characteristics and aspects are involved in the social platforms for collective intelligence. The topics include social network theory and modeling, graph mining, query log processing, learning to rank, recommender systems, human computation, etc. The tutorial is prepared for machine learning, web mining, and information retrieval researchers who are interested in computational approaches to social computing.