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Content Provider | IEEE Xplore Digital Library |
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Author | Chenhao Xie Deqing Yang Jingrui He Yanghua Xiao |
Copyright Year | 2015 |
Description | Author affiliation: Arizona State Univ., Tempe, AZ, USA (Jingrui He) || Sch. of Comput. Sci., Fudan Univ., Shanghai, China (Chenhao Xie; Deqing Yang; Yanghua Xiao) |
Abstract | Given the plethora of social networking sites, it can be difficult for users to browse too many sites and discover social friends. For example, for a new diabetes patient, how can s/he find the users with similar symptoms on different dedicated sites and form supporting groups with them? Since different sites may use different vocabularies, this problem is challenging to match users across different sites. To address it, in this paper, we present a tool to demonstrate how to construct a virtual social network across multiple social networking sites. Specifically, it uses bipartite graphs to represent the relation ships between users and their posts' keywords in each site, it bridges the gap between different vocabularies of different sites based on their semantic relatedness through concept-based interpretations, and it uses an efficient propagation algorithm to obtain the similarity between users from different sites, which can be used to construct the cross-site virtual social network. |
Starting Page | 1660 |
Ending Page | 1663 |
File Size | 269992 |
Page Count | 4 |
File Format | |
ISSN | 23759259 |
e-ISBN | 9781467384933 |
DOI | 10.1109/ICDMW.2015.98 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2015-11-14 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Vocabulary virtual social network Social network services Semantics semantic matching Encyclopedias User interfaces cross-site Diabetes Bipartite graph graph propagation |
Content Type | Text |
Resource Type | Article |
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