Raison D'etre Object: A Cyber-Hearth That Catalyzes Face-to-Face Informal Communication
EDCIS '02 Proceedings of the First International Conference on Engineering and Deployment of Cooperative Information Systems
The Journal of Machine Learning Research
The traveling café: a communication encouraging system for partitioned offices
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Grounding of word meanings in multimodal concepts using LDA
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Term Weighting Schemes for Emerging Event Detection
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
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In recent years, microblogging is popular among people and informal communication becomes important in various communities. Therefore, a number of Web communication tools are developed to facilitate informal communication. In this paper, focusing on microblogging service, Twitter, we develop a user recommendation engine which extracts latent topics of users based on followings, lists, mentions and RTs. This recommendation algorithm is based on Latent Dirichlet Allocation (LDA) and KL divergence between two users' latent topics. This algorithm hypothesizes that the users have latent connection if the distance calculated by KL divergence is short. Additionally, we performed an experiment to evaluate the effectiveness of the algorithm, and this showed that there is correlation between the distance and user's preference obtained through questionnaire.