Title: Social networking meets recommender systems: survey

Authors: Guandong Xu; Zhiang Wu; Yanchun Zhang; Jie Cao

Addresses: Advanced Analytics Institute, University of Technology, Sydney, Australia ' Jiangsu Provincial Key Laboratory of E-Business, Nanjing University of Finance and Economics, Nanjing, China ' School of Computer Science and Mathematics, Victoria University, Melbourne, Australia ' Jiangsu Provincial Key Laboratory of E-Business, Nanjing University of Finance and Economics, Nanjing, China

Abstract: Today, the emergence of web-based communities and hosted services such as social networking sites, wikis and folksonomies, brings in tremendous freedom of web autonomy and facilitate collaboration and knowledge sharing between users. Along with the interaction between users and computers, social media is rapidly becoming an important part of our digital experience, ranging from digital textual information to diverse multimedia forms. These aspects and characteristics constitute of the core of second generation of web. Social networking (SN) and recommender system (RS) are two hot and popular topics in the current Web 2.0 era, where the former emphasises the generation, dissemination and evolution of user relations, and the latter focuses on the use of collective preferences of users so as to provide the better experience and loyalty of users in various web applications. Leveraging user social connections is able to alleviate the common problems of sparsity and cold-start encountered in RS. This paper aims to summarise the research progresses and findings in these two areas and showcase the empowerment of integrating these two kinds of research strengths.

Keywords: social networking; recommendation systems; community detection; collaborative filtering; matrix factorisation; social recommender systems; user social connections.

DOI: 10.1504/IJSNM.2015.069773

International Journal of Social Network Mining, 2015 Vol.2 No.1, pp.64 - 100

Available online: 11 Jun 2015 *

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