Social networking meets recommender systems: survey

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.

[1]  Chao Liu,et al.  Recommender systems with social regularization , 2011, WSDM '11.

[2]  Wei Chen,et al.  Efficient influence maximization in social networks , 2009, KDD.

[3]  Henry Lieberman,et al.  Letizia: An Agent That Assists Web Browsing , 1995, IJCAI.

[4]  Yanchun Zhang,et al.  Effectively Finding Relevant Web Pages from Linkage Information , 2003, IEEE Trans. Knowl. Data Eng..

[5]  Michael R. Lyu,et al.  SoRec: social recommendation using probabilistic matrix factorization , 2008, CIKM '08.

[6]  Tanya Y. Berger-Wolf,et al.  A framework for community identification in dynamic social networks , 2007, KDD '07.

[7]  Matthew Richardson,et al.  Yes, there is a correlation: - from social networks to personal behavior on the web , 2008, WWW.

[8]  Ramakrishnan Srikant,et al.  Mining sequential patterns , 1995, Proceedings of the Eleventh International Conference on Data Engineering.

[9]  Jimeng Sun,et al.  Social influence analysis in large-scale networks , 2009, KDD.

[10]  Francesco Bonchi,et al.  Cold start link prediction , 2010, KDD.

[11]  David Liben-Nowell,et al.  The link-prediction problem for social networks , 2007 .

[12]  Bradley N. Miller,et al.  GroupLens: applying collaborative filtering to Usenet news , 1997, CACM.

[13]  R. J. Mokken,et al.  Cliques, clubs and clans , 1979 .

[14]  Vijay Mahajan,et al.  New Product Diffusion Models in Marketing: A Review and Directions for Research: , 1990 .

[15]  A. Clauset Finding local community structure in networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Philip S. Yu,et al.  Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[17]  Dan Cosley,et al.  Inferring social ties from geographic coincidences , 2010, Proceedings of the National Academy of Sciences.

[18]  Huan Liu,et al.  Identifying Evolving Groups in Dynamic Multimode Networks , 2012, IEEE Transactions on Knowledge and Data Engineering.

[19]  Edith Cohen,et al.  Improving end-to-end performance of the Web using server volumes and proxy filters , 1998, SIGCOMM '98.

[20]  Christophe Diot,et al.  Dissemination in opportunistic social networks: the role of temporal communities , 2012, MobiHoc '12.

[21]  Paul B. Slater,et al.  Established Clustering Procedures for Network Analysis , 2008, ArXiv.

[22]  John C. S. Lui,et al.  On Modeling Product Advertisement in Large-Scale Online Social Networks , 2012, IEEE/ACM Transactions on Networking.

[23]  Yu Zheng,et al.  Computing with Spatial Trajectories , 2011, Computing with Spatial Trajectories.

[24]  Michael R. Lyu,et al.  Learning to recommend with social trust ensemble , 2009, SIGIR.

[25]  Andreas Hotho,et al.  Tag Recommendations in Folksonomies , 2007, LWA.

[26]  Mohammad Al Hasan,et al.  A Survey of Link Prediction in Social Networks , 2011, Social Network Data Analytics.

[27]  Martin Ester,et al.  TrustWalker: a random walk model for combining trust-based and item-based recommendation , 2009, KDD.

[28]  Aniket Kittur,et al.  Bridging the gap between physical location and online social networks , 2010, UbiComp.

[29]  Frederico Araújo Durão,et al.  Extending a hybrid tag-based recommender system with personalization , 2010, SAC '10.

[30]  T. Vicsek,et al.  Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.

[31]  Mehran Sahami,et al.  Evaluating similarity measures: a large-scale study in the orkut social network , 2005, KDD '05.

[32]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[33]  Pattie Maes,et al.  Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.

[34]  Philip S. Yu,et al.  Dirichlet Process Based Evolutionary Clustering , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[35]  E. Levina,et al.  Community extraction for social networks , 2010, Proceedings of the National Academy of Sciences.

[36]  Jon Kleinberg,et al.  Maximizing the spread of influence through a social network , 2003, KDD '03.

[37]  Georg Groh,et al.  Recommendations in taste related domains: collaborative filtering vs. social filtering , 2007, GROUP.

[38]  Xindong Wu,et al.  SiteHelper: A Localized Agent That Helps Incremental Exploration of the World Wide Web , 1997, Comput. Networks.

[39]  Tao Luo,et al.  Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization , 2004, Data Mining and Knowledge Discovery.

[40]  Aravind Srinivasan,et al.  Modelling disease outbreaks in realistic urban social networks , 2004, Nature.

[41]  Harald Steck,et al.  Circle-based recommendation in online social networks , 2012, KDD.

[42]  Chun Chen,et al.  Document recommendation in social tagging services , 2010, WWW '10.

[43]  Jon Kleinberg,et al.  Authoritative sources in a hyperlinked environment , 1998, SODA '98.

[44]  John Riedl,et al.  An Algorithmic Framework for Performing Collaborative Filtering , 1999, SIGIR Forum.

[45]  Lars Schmidt-Thieme,et al.  Learning optimal ranking with tensor factorization for tag recommendation , 2009, KDD.

[46]  E. Rogers Diffusion of Innovations , 1962 .

[47]  Jaideep Srivastava,et al.  Creating adaptive Web sites through usage-based clustering of URLs , 1999, Proceedings 1999 Workshop on Knowledge and Data Engineering Exchange (KDEX'99) (Cat. No.PR00453).

[48]  Mark E. J. Newman,et al.  Stochastic blockmodels and community structure in networks , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[49]  Kyumin Lee,et al.  Uncovering social spammers: social honeypots + machine learning , 2010, SIGIR.

[50]  Vern Paxson,et al.  @spam: the underground on 140 characters or less , 2010, CCS '10.

[51]  Ioannis Konstas,et al.  On social networks and collaborative recommendation , 2009, SIGIR.

[52]  Lars Backstrom,et al.  Find me if you can: improving geographical prediction with social and spatial proximity , 2010, WWW '10.

[53]  Martin Ester,et al.  A matrix factorization technique with trust propagation for recommendation in social networks , 2010, RecSys '10.

[54]  Oren Etzioni,et al.  Adaptive Web Sites: Conceptual Cluster Mining , 1999, IJCAI.

[55]  Dong Xu,et al.  Time Constrained Influence Maximization in Social Networks , 2012, 2012 IEEE 12th International Conference on Data Mining.

[56]  Jure Leskovec,et al.  Friendship and mobility: user movement in location-based social networks , 2011, KDD.

[57]  Chun Chen,et al.  Personalized tag recommendation using graph-based ranking on multi-type interrelated objects , 2009, SIGIR.

[58]  Pang-Ning Tan,et al.  Measuring the effects of preprocessing decisions and network forces in dynamic network analysis , 2009, KDD.

[59]  Srinivasan Parthasarathy,et al.  Local Probabilistic Models for Link Prediction , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

[60]  Olivier Serrat Social Network Analysis , 2009 .

[61]  Yihong Gong,et al.  A Bayesian Approach Toward Finding Communities and Their Evolutions in Dynamic Social Networks , 2009, SDM.

[62]  Yi-Cheng Zhang,et al.  Personalized Recommendation via Integrated Diffusion on User-Item-Tag Tripartite Graphs , 2009, ArXiv.

[63]  ChengXiang Zhai,et al.  Discovering evolutionary theme patterns from text: an exploration of temporal text mining , 2005, KDD '05.

[64]  Philip S. Yu,et al.  GraphScope: parameter-free mining of large time-evolving graphs , 2007, KDD '07.

[65]  Hisashi Kashima,et al.  Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs , 2010, ECML/PKDD.

[66]  Thomas Hofmann,et al.  Latent semantic models for collaborative filtering , 2004, TOIS.

[67]  Jimeng Sun,et al.  Cross-domain collaboration recommendation , 2012, KDD.

[68]  Oren Etzioni,et al.  Adaptive Web Sites: Automatically Synthesizing Web Pages , 1998, AAAI/IAAI.

[69]  Hui Xiong,et al.  An energy-efficient mobile recommender system , 2010, KDD.

[70]  Jure Leskovec,et al.  Information diffusion and external influence in networks , 2012, KDD.

[71]  Peter Mika Ontologies Are Us: A Unified Model of Social Networks and Semantics , 2005, International Semantic Web Conference.

[72]  Stanley Boykin,et al.  Machine learning of event segmentation for news on demand , 2000, CACM.

[73]  Panagiotis Symeonidis,et al.  A Unified Framework for Providing Recommendations in Social Tagging Systems Based on Ternary Semantic Analysis , 2010, IEEE Transactions on Knowledge and Data Engineering.

[74]  Ramakrishnan Srikant,et al.  Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.

[75]  Jacob Goldenberg,et al.  Talk of the Network: A Complex Systems Look at the Underlying Process of Word-of-Mouth , 2001 .

[76]  Yanchun Zhang,et al.  SemRec: A Semantic Enhancement Framework for Tag Based Recommendation , 2011, AAAI.

[77]  Le Yu,et al.  Adaptive social similarities for recommender systems , 2011, RecSys '11.

[78]  Wei Chen,et al.  Scalable influence maximization for prevalent viral marketing in large-scale social networks , 2010, KDD.

[79]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[80]  Yehuda Koren,et al.  Factorization meets the neighborhood: a multifaceted collaborative filtering model , 2008, KDD.

[81]  Weiguo Fan,et al.  Learning to advertise , 2006, SIGIR.

[82]  Huan Liu,et al.  Community detection via heterogeneous interaction analysis , 2012, Data Mining and Knowledge Discovery.

[83]  Wei-Ying Ma,et al.  Recommending friends and locations based on individual location history , 2011, ACM Trans. Web.

[84]  David Lazer,et al.  Inferring friendship network structure by using mobile phone data , 2009, Proceedings of the National Academy of Sciences.

[85]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[86]  Chien Chin Chen,et al.  TSCAN: A Content Anatomy Approach to Temporal Topic Summarization , 2012, IEEE Transactions on Knowledge and Data Engineering.

[87]  Brian W. Kernighan,et al.  An efficient heuristic procedure for partitioning graphs , 1970, Bell Syst. Tech. J..

[88]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[89]  Mark S. Granovetter Threshold Models of Collective Behavior , 1978, American Journal of Sociology.

[90]  Martin G. Everett,et al.  Models of core/periphery structures , 2000, Soc. Networks.

[91]  Vipin Kumar,et al.  Hypergraph Based Clustering in High-Dimensional Data Sets: A Summary of Results , 1998, IEEE Data Eng. Bull..

[92]  Yun Chi,et al.  Analyzing communities and their evolutions in dynamic social networks , 2009, TKDD.

[93]  Lars Schmidt-Thieme,et al.  Tag-aware recommender systems by fusion of collaborative filtering algorithms , 2008, SAC '08.

[94]  Matthew E. Kahn,et al.  Sprawl and Urban Growth , 2003 .

[95]  Guofei Gu,et al.  Analyzing spammers' social networks for fun and profit: a case study of cyber criminal ecosystem on twitter , 2012, WWW.

[96]  Mohammad Al Hasan,et al.  Link prediction using supervised learning , 2006 .

[97]  Yanchun Zhang,et al.  Web communities - analysis and construction , 2005 .

[98]  Markus Jakobsson,et al.  Social phishing , 2007, CACM.

[99]  Hui Xiong,et al.  Adapting the right measures for K-means clustering , 2009, KDD.

[100]  Soumen Chakrabarti,et al.  Data mining for hypertext: a tutorial survey , 2000, SKDD.

[101]  Gueorgi Kossinets,et al.  Empirical Analysis of an Evolving Social Network , 2006, Science.

[102]  Sandra Sudarsky,et al.  Massive Quasi-Clique Detection , 2002, LATIN.

[103]  Thorsten Joachims,et al.  Web Watcher: A Tour Guide for the World Wide Web , 1997, IJCAI.

[104]  Andreas Hotho,et al.  FolkRank : A Ranking Algorithm for Folksonomies , 2006, LWA.

[105]  Foster Provost,et al.  Audience selection for on-line brand advertising: privacy-friendly social network targeting , 2009, KDD.

[106]  Hector Garcia-Molina,et al.  Social tag prediction , 2008, SIGIR '08.

[107]  Jaideep Srivastava,et al.  Web usage mining: discovery and applications of usage patterns from Web data , 2000, SKDD.

[108]  Edward Y. Chang,et al.  AdHeat: an influence-based diffusion model for propagating hints to match ads , 2010, WWW '10.

[109]  Hendrik Blockeel,et al.  Web mining research: a survey , 2000, SKDD.

[110]  Houfeng Wang,et al.  Entity-centric topic-oriented opinion summarization in twitter , 2012, KDD.

[111]  Karl Aberer,et al.  Neighborhood-Based Tag Prediction , 2009, ESWC.

[112]  Georgia Koutrika,et al.  Combating spam in tagging systems: An evaluation , 2008, TWEB.

[113]  Edward Y. Chang,et al.  Mining blog stories using community-based and temporal clustering , 2006, CIKM '06.

[114]  Ralf Krestel,et al.  Latent dirichlet allocation for tag recommendation , 2009, RecSys '09.

[115]  Tom M. Mitchell,et al.  Learning to Extract Symbolic Knowledge from the World Wide Web , 1998, AAAI/IAAI.

[116]  Xin Li,et al.  Tag-based social interest discovery , 2008, WWW.

[117]  Bamshad Mobasher,et al.  Personalized recommendation in social tagging systems using hierarchical clustering , 2008, RecSys '08.

[118]  Michael J. Muller,et al.  Make new friends, but keep the old: recommending people on social networking sites , 2009, CHI.

[119]  Maurice D. Mulvenna,et al.  Discovering Internet marketing intelligence through online analytical web usage mining , 1998, SGMD.

[120]  A. Raftery,et al.  Model‐based clustering for social networks , 2007 .

[121]  Mark S. Granovetter The Strength of Weak Ties , 1973, American Journal of Sociology.

[122]  Yoshihiro Yamanishi,et al.  propagation: A fast semisupervised learning algorithm for link prediction , 2009 .