GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The Journal of Machine Learning Research
Adapting ranking SVM to document retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Google news personalization: scalable online collaborative filtering
Proceedings of the 16th international conference on World Wide Web
EigenRank: a ranking-oriented approach to collaborative filtering
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
SoRec: social recommendation using probabilistic matrix factorization
Proceedings of the 17th ACM conference on Information and knowledge management
Matchbox: large scale online bayesian recommendations
Proceedings of the 18th international conference on World wide web
Regression-based latent factor models
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting user similarity based on rated-item pools for improved user-based collaborative filtering
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
Short and tweet: experiments on recommending content from information streams
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
BPR: Bayesian personalized ranking from implicit feedback
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Automatic generation of personalized annotation tags for Twitter users
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Recommending twitter users to follow using content and collaborative filtering approaches
Proceedings of the fourth ACM conference on Recommender systems
Discovering users' topics of interest on twitter: a first look
AND '10 Proceedings of the fourth workshop on Analytics for noisy unstructured text data
An empirical study on learning to rank of tweets
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Contextual recommendation based on text mining
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Like like alike: joint friendship and interest propagation in social networks
Proceedings of the 20th international conference on World wide web
Finding useful users on twitter: twittomender the followee recommender
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Recognizing named entities in tweets
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Interactive group suggesting for Twitter
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Who should share what?: item-level social influence prediction for users and posts ranking
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Fast context-aware recommendations with factorization machines
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Co-factorization machines: modeling user interests and predicting individual decisions in Twitter
Proceedings of the sixth ACM international conference on Web search and data mining
Personalized time-aware tweets summarization
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Informational friend recommendation in social media
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Combining latent factor model with location features for event-based group recommendation
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Linking named entities in Tweets with knowledge base via user interest modeling
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Choosing which message to publish on social networks: a contextual bandit approach
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Using emotional context from article for contextual music recommendation
Proceedings of the 21st ACM international conference on Multimedia
Diffusion-aware personalized social update recommendation
Proceedings of the 7th ACM conference on Recommender systems
Combining prestige and relevance ranking for personalized recommendation
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Mining user interest and its evolution for recommendation on the micro-blogging system
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Social influence locality for modeling retweeting behaviors
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Twitter has rapidly grown to a popular social network in recent years and provides a large number of real-time messages for users. Tweets are presented in chronological order and users scan the followees' timelines to find what they are interested in. However, an information overload problem has troubled many users, especially those with many followees and thousands of tweets arriving every day. In this paper, we focus on recommending useful tweets that users are really interested in personally to reduce the users' effort to find useful information. Many kinds of information on Twitter are available for helping recommendation, including the user's own tweet history, retweet history and social relations between users. We propose a method of making tweet recommendations based on collaborative ranking to capture personal interests. It can also conveniently integrate the other useful contextual information. Our final method considers three major elements on Twitter: tweet topic level factors, user social relation factors and explicit features such as authority of the publisher and quality of the tweet. The experiments show that all the proposed elements are important and our method greatly outperforms several baseline methods.