Abstract
Modeling users’ topical interests on microblog is an important but challenging task. In this paper, we propose User Message Model (UMM), a hierarchical topic model specially designed for user modeling on microblog. In UMM, users and their messages are modeled by a hierarchy of topics. Thus, it has the ability to 1) deal with both the data sparseness and the topic diversity problems which previous methods suffer from, and 2) jointly model users and messages in a unified framework. Furthermore, UMM can be easily distributed to handle large-scale datasets. Experimental results on both Sina Weibo and Twitter datasets show that UMM can effectively model users’ interests on microblog. It can achieve better results than previous methods in topic discovery and message recommendation. Experimental results on a large-scale Twitter dataset, containing about 2 million users and 50 million messages, further demonstrate the scalability and efficiency of distributed UMM.
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Wang, Q., Xu, J., Li, H. (2014). User Message Model: A New Approach to Scalable User Modeling on Microblog. In: Jaafar, A., et al. Information Retrieval Technology. AIRS 2014. Lecture Notes in Computer Science, vol 8870. Springer, Cham. https://doi.org/10.1007/978-3-319-12844-3_18
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DOI: https://doi.org/10.1007/978-3-319-12844-3_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12843-6
Online ISBN: 978-3-319-12844-3
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