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ACM Transactions on Information Systems (TOIS)
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Topic-conditioned novelty detection
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The role of spatial contextual factors in mobile personalization at large sports events
Personal and Ubiquitous Computing
SocialSearchBrowser: a novel mobile search and information discovery tool
Proceedings of the 15th international conference on Intelligent user interfaces
Introduction to Mobile Information Retrieval
IEEE Intelligent Systems
Music Recommendation Using Content and Context Information Mining
IEEE Intelligent Systems
IEEE Intelligent Systems
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
Speak little and well: recommending conversations in online social streams
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Twitinfo: aggregating and visualizing microblogs for event exploration
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Personal and Ubiquitous Computing
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Mobile microblog browsing is inconvenient due to the limitations of mobile devices. Therefore, it is important to effectively retrieve relevant and timely microblog content that caters to the information need of mobile users. In this paper, we first present the findings from a large-scale study on the relationship between microblog content and user context. Then, we show a system that detects local microblog topics, estimates user interests and selects user-preferred topics. The system employs user context to detect microblog topics and post-processes the topics for finding user-preferred content. We exploit time, location, browsing history, social relationship and activity as user context. The effectiveness of our approach is evaluated against several baseline algorithms for investigating the impact of user context on the relevance of retrieved topics. According to our experimental results, the approach enhances the relevance of topics by 24%, compared to the baseline approaches. Thus, we expect that the proposed approach is helpful in advancing mobile information retrieval.