A content-based approach for user profile modeling and matching on social networks

被引：0
作者：
Van Le, Thanh [1 ]
Truong, Trong Nghia [1 ]
Pham, Tran Vu [1 ]
机构：
[1] Ho Chi Minh City University of Technology, VNU-HCM, No 268, Ly Thuong Kiet Street, District 10, Ho Chi Minh City
来源：
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 2014年 / 8875卷
关键词：
Hidden topics; LDA; Pretopology; Profile matching; Social networks;
D O I：
10.1007/978-3-319-13365-2_21
中图分类号：
学科分类号：
摘要：
The development of social networks gives billions of users the convenience and the ability to quickly connect and interact with others for raising opinions, sharing news, photos, etc. On the road for building tools to extend friend circles as large as possible, one of themost important functions of a social network is the recommendation which proposes a group of people having some common characteristics or relations. A majority of social networks have friend suggestion function based on mutual friends. However, this suggestion mechanism does not care much about the actual interests of the users hidden in his comments, posts or activities. This paper aims to propose a profile modeling and matching approach based on Latent Dirichlet Allocation (LDA) and pretopological-based multi-criteria aggregation to explore topics that exist in user posts on a social network. We explored interesting points of pretopology concepts - a mathematical tool - and applied them for better solving the raised problem. This approach allows us to find out users who have similar interests and also other information involving user profiles. © Springer International Publishing Switzerland 2014.
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页码：232 / 243
页数：11
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