标题:A User Adaptive Model for Followee Recommendation on Twitter
作者:Liu, Yang; Chen, Xuan; Li, Sujian; Wang, Liang
通讯作者:Li, Sujian
作者机构:[Liu, Yang; Li, Sujian; Wang, Liang] Peking Univ, MOE, Key Lab Computat Linguist, Beijing, Peoples R China.; [Chen, Xuan] Shandong Univ Polit Sci & 更多
会议名称:5th International Conference on Natural Language Processing and Chinese Computing (NLPCC) / 24th International Conference on Computer Processing of Oriental Languages (ICCPOL)
会议日期:DEC 02-06, 2016
来源:NATURAL LANGUAGE UNDERSTANDING AND INTELLIGENT APPLICATIONS (NLPCC 2016)
出版年:2016
卷:10102
页码:425-436
DOI:10.1007/978-3-319-50496-4_35
摘要:On the Twitter platform, an effective followee recommendation system is helpful to connecting users in a satisfactory manner. Topological relations and tweets content are two main factors considered in a followee recommendation system. However, how to combine these two kinds of information in a uniform framework is still an open problem. In this paper, we propose to combine deep learning techniques and collaborative information to explore the user representations latent behind the topology and content. Over two kinds of user representations (i.e., topology representation and content representation), we design an adaptive layer to dynamically leverage the contribution of topology and content to recommending followees, which changes the situation where the contribution weights are usually predefined. Experiments on a real-world Twitter dataset show that our proposed model provides more satisfying recommendation results than state-of-the-art methods.
收录类别:CPCI-S;EI;SCOPUS
Scopus被引频次:1
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85004144080&doi=10.1007%2f978-3-319-50496-4_35&partnerID=40&md5=900b871fb483f5fd96287e5705f1715b
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