Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
The Journal of Machine Learning Research
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Community evolution in dynamic multi-mode networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalized recommendation in social tagging systems using hierarchical clustering
Proceedings of the 2008 ACM conference on Recommender systems
Collaborative filtering for orkut communities: discovery of user latent behavior
Proceedings of the 18th international conference on World wide web
Co-evolution of social and affiliation networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Sifting micro-blogging stream for events of user interest
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Using twitter to recommend real-time topical news
Proceedings of the third ACM conference on Recommender systems
Personalized social search based on the user's social network
Proceedings of the 18th ACM conference on Information and knowledge management
Collaborative filtering with temporal dynamics
Communications of the ACM
Characterizing debate performance via aggregated twitter sentiment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Pusic: musicalize microblog messages for summarization and exploration
Proceedings of the 19th international conference on World wide web
PET: a statistical model for popular events tracking in social communities
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Recommending twitter users to follow using content and collaborative filtering approaches
Proceedings of the fourth ACM conference on Recommender systems
Discovering User Interest on Twitter with a Modified Author-Topic Model
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Improving user interest inference from social neighbors
Proceedings of the 20th ACM international conference on Information and knowledge management
Effects of user similarity in social media
Proceedings of the fifth ACM international conference on Web search and data mining
Collaborative personalized tweet recommendation
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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Different users have different needs, it is increasingly difficult to recommend interested topics to them. The micro-blogging system can expose user interests from individual behaviors along with his/her social connections. It also offers an opportunity to investigate how a large-scale social system recommends personal preferences according to the temporal, spatial and topical aspects of users activity. Here we focus on the problem of mining user interest and modeling its evolution on the micro-blogging system for recommendation. We learn the user preference on topics from the visited micro-bloggings as user interest using text mining techniques. We then extend this concept with user's social connection on different topics. Moreover, we study the evolution of the user interest model and finally recommend the most preferred micro-bloggings to a user. Experiments on a large scale of micro-blogging dataset shows that our model outperforms traditional approaches and achieves considerable performance on recommending interested posts to a user.