Dynamic circle recommendation: A probabilistic model

Fan Kai Chou, Meng Fen Chiang, Yi Cheng Chen, Wen Chih Peng

研究成果: 雜誌貢獻會議論文同行評審


This paper presents a novel framework for dynamic circle recommendation for a query user at a given time point from historical communication logs. We identify the fundamental factors that govern interactions and aim to automatically form dynamic circle for scenarios, such as, who should I dial to in the early morning? whose mail would I reply first at midnight? We develop a time-sensitive probabilistic model (TCircleRank) that not only captures temporal tendencies between the query user and candidate friends but also blends frequency and recency into group formation. We also utilize the model to support two types of dynamic circle recommendation: Seedset Generation: single-interaction suggestion and Circle Suggestion: multiple interactions suggestion. We further present approaches to infer relevant time interval in determining circles for a query user at a given time. Experimental results on Enron dataset, Call Detail Records and Reality Mining Data prove the effectiveness of dynamic circle recommendation using TCircleRank.

頁(從 - 到)25-37
期刊Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
8444 LNAI
發行號PART 2
出版狀態已出版 - 2014
事件18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2014 - Tainan, Taiwan
持續時間: 13 5月 201416 5月 2014


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