GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
A vector space model for automatic indexing
Communications of the ACM
Information Filtering: Overview of Issues, Research and Systems
User Modeling and User-Adapted Interaction
Twitter power: Tweets as electronic word of mouth
Journal of the American Society for Information Science and Technology
A survey of collaborative filtering techniques
Advances in Artificial Intelligence
A method for personalized ranking of items based on similarity between Twitter users
Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication
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In this paper, we introduce an agent for recommending information to a user on Twitter, which is one of the most popular microblogging services. For recommending sufficient information for a user, it is important to extract automatically user's interest with accuracy and to collect new information which interests and attracts the user. The agent that is introduced in this paper extracts automatically user's interests from tweets on the timeline of the user and finds the web sites that would provide new information which interests the user from the tweets. The agent selects recommending information from the web sites and posts it on the user's timeline. Experimental results show that our agent is able to recommend sufficient information for users of Twitter in a natural manner.