Referral Web: combining social networks and collaborative filtering
Communications of the ACM
Mining the most interesting rules
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Computer Supported Social Networking For Augmenting Cooperation
Computer Supported Cooperative Work
Recommending collaboration with social networks: a comparative evaluation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Mining Indirect Associations in Web Data
WEBKDD '01 Revised Papers from the Third International Workshop on Mining Web Log Data Across All Customers Touch Points
Proceedings of the 15th international conference on World Wide Web
Using ontology network analysis for research document recommendation
Expert Systems with Applications: An International Journal
Collaboration over time: characterizing and modeling network evolution
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
DBconnect: mining research community on DBLP data
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
ArnetMiner: extraction and mining of academic social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Make new friends, but keep the old: recommending people on social networking sites
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Behavioral profiles for advanced email features
Proceedings of the 18th international conference on World wide web
Identifying Social Communities by Frequent Pattern Mining
IV '09 Proceedings of the 2009 13th International Conference Information Visualisation
FriendSensing: recommending friends using mobile phones
Proceedings of the third ACM conference on Recommender systems
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
Mining Indirect Association Rules for Web Recommendation
International Journal of Applied Mathematics and Computer Science
Suggesting friends using the implicit social graph
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Virus Propagation Modeling in Facebook
ASONAM '10 Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining
CollabSeer: a search engine for collaboration discovery
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Who needs Facebook or Google+ anyway: privacy and sociality in social network sites
Proceedings of the 7th ACM workshop on Digital identity management
Understanding and combating link farming in the twitter social network
Proceedings of the 21st international conference on World Wide Web
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Collaborative research is increasingly important and popular in academic circles. However for young researchers identifying new research collaborators to form joint research and analyzing the level of cooperation of the current partners can be a very complex task. Thus recommendation of new collaborations would be important for young researchers. This paper presents a new approach to recommend collaborators in an academic social network using the co-authorship network. We propose a weighted indirect rule mining approach using a novel weighting mechanism called sociability.