Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/134925
Title: MULTIMEDIA USER PROFILING IN ONLINE SOCIAL NETWORKS
Authors: GENG XUE
Keywords: user profiling, online social networks, multimedia, deep learning, feature learning, image processing
Issue Date: 11-Aug-2016
Source: GENG XUE (2016-08-11). MULTIMEDIA USER PROFILING IN ONLINE SOCIAL NETWORKS. ScholarBank@NUS Repository.
Abstract: Online Social Network Services (OSNs) provide popular platforms to build social networks and enhance social relationships among people who share common interests, activities, backgrounds and real-life connections. Over the years, many multimedia- based OSNs such as Pinterest, Flickr and Youtube have emerged. Furthermore, people have been sharing more and more multimedia contents over the years. However, the exponentially increasing media contents will make it difficult for service providers to tailor media contents to accommodate specific individuals. To address the issue, this thesis attempts to undertake the task of user profiling in OSNs. To the best of our knowledge, most existing approaches only focus on mining textual information to construct user profiles, while overlook the abundant shared media contents. This thesis, taking Pinterest as an example, focuses on developing effective and efficient approaches to model user profiles, by exploring rich user-generated multimedia contents including images, texts, together with domain knowledge.
URI: http://scholarbank.nus.edu.sg/handle/10635/134925
Appears in Collections:Ph.D Theses (Open)

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