KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Study on Tag, Trust and Probability Matrix Factorization Based Social Network Recommendation

  • Liu, Zhigang (Control Technology Institute, Wuxi Institute of Technology) ;
  • Zhong, Haidong (Logistics and e-commerce school, Zhejiang Wanli University)
  • Received : 2017.06.21
  • Accepted : 2017.11.08
  • Published : 2018.05.31
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Abstract

In recent years, social network related applications such as WeChat, Facebook, Twitter and so on, have attracted hundreds of millions of people to share their experience, plan or organize, and attend social events with friends. In these operations, plenty of valuable information is accumulated, which makes an innovative approach to explore users' preference and overcome challenges in traditional recommender systems. Based on the study of the existing social network recommendation methods, we find there is an abundant information that can be incorporated into probability matrix factorization (PMF) model to handle challenges such as data sparsity in many recommender systems. Therefore, the research put forward a unified social network recommendation framework that combine tags, trust between users, ratings with PMF. The uniformed method is based on three existing recommendation models (SoRecUser, SoRecItem and SoRec), and the complexity analysis indicates that our approach has good effectiveness and can be applied to large-scale datasets. Furthermore, experimental results on publicly available Last.fm dataset show that our method outperforms the existing state-of-art social network recommendation approaches, measured by MAE and MRSE in different data sparse conditions.

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References

  1. Millen D R, Feinberg J, "Using social tagging to improve social navigation," in Proc. of the Workshop on the Social Navigation and Community based Adaptation Technologies, June 20-20, 2006.
  2. Wu L, Chen E, Liu Q, Xu L, Bao T, Zhang L, "Leveraging tagging for neighborhood-aware probabilistic matrix factorization," in Proc. of the 21st ACM international conference on Information and knowledge management, pp. 1854-1858, October 29 - November 02, 2012.
  3. Zhou T C, Ma H, King I, Lyu M R, "TagRec: Leveraging Tagging Wisdom for Recommendation," in Proc. of the 2009 International Conference on Computational Science and Engineering, pp. 194-199, Augst 29-31, 2009.
  4. MA H., "Learning to Recommend (Ph.D thesis)," Hong Kong; The Chinese University of Hong Kong, 2009.
  5. Yu Z, Wang C, Bu J, Wang X, Wu Y, Chen C, "Friend recommendation with content spread enhancement in social networks," Information Sciences, vol. 309, pp. 102-118, 2015. https://doi.org/10.1016/j.ins.2015.03.012
  6. Yom-Tov E, Diaz F, "Out of sight, not out of mind: on the effect of social and physical detachment on information need," in Proc. of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, pp. 385-394, July 24-28, 2011.
  7. Ma H, King I, Lyu M R, "Learning to recommend with social trust ensemble," in Proc. of the 32nd international ACM SIGIR conference on Research and development in information retrieval, pp. 203-210, July 19-23, 2009.
  8. Cha M, Mislove A, Gummadi K P, "A measurement-driven analysis of information propagation in the flickr social network," in Proc. of the 18th international conference on World wide web, pp. 721-730, April 20-24, 2009.
  9. Jamali M, Ester M, "A matrix factorization technique with trust propagation for recommendation in social networks," in Proc. of the fourth ACM conference on Recommender systems, pp. 135-142, September 26-30, 2010.
  10. Zlatic V, Ghoshal G, Caldarelli G, "Hypergraph topological quantities for tagged social networks," Physical Review E, vol. 80, no. 3, pp. 1-8, 2009.
  11. Hung C-C, Huang Y-C, Hsu J Y-j, Wu D K-C, "Tag-based user profiling for social media recommendation," in Proc. of the Workshop on Intelligent Techniques for Web Personalization & Recommender Systems at AAAI, pp. 49-55, July 13-14, 2008.
  12. Tibely G, Pollner P, Vicsek T, Palla G, "Extracting tag hierarchies," PloS one, vol. 8, no. 12, pp. e84133, 2013. https://doi.org/10.1371/journal.pone.0084133
  13. Symeonidis P, Nanopoulos A, Manolopoulos Y, "A unified framework for providing recommendations in social tagging systems based on ternary semantic analysis," IEEE Transactions on Knowledge and Data Engineering, vol. 22, no. 2, pp. 179-192, 2010. https://doi.org/10.1109/TKDE.2009.85
  14. Spyns P, De Moor A, Vandenbussche J, Meersman R, "From folksologies to ontologies: How the twain meet," in Proc. of the OTM Confederated International Conferences on the Move to Meaningful Internet Systems, pp. 738-755, October 29-November 3, 2006.
  15. Iturrioz J, Diaz O, Azpeitia I, "Reactive tags: Associating behaviour to prescriptive tags," in Proc. of the 22nd ACM conference on Hypertext and hypermedia, pp. 191-200, June 06-09, 2011.
  16. Ames M, Naaman M, "Why we tag: motivations for annotation in mobile and online media," in Proc. of the SIGCHI conference on Human factors in computing systems, pp. 971-980, April 28 - May 3, 2007.
  17. Golder S A, Huberman B A, "Usage patterns of collaborative tagging systems," Journal of information science, vol. 32, no. 2, pp. 198-208, 2006. https://doi.org/10.1177/0165551506062337
  18. Heymann P, Ramage D, Garcia-Molina H, "Social tag prediction," in Proc. of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, pp. 531-538, July 20-24, 2008.
  19. Chi C, Zhou M X, Yang M, Xiao W, Yu Y, Sun X, "Dandelion: Supporting coordinated, collaborative authoring in Wikis," in Proc. of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1199-1202, April 10-15, 2010.
  20. Zhong H, Zhang S, Wang Y, Shu Y, "Study on Directed Trust Graph Based Recommendation for E-commerce System," INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, vol. 9, no. 4, pp. 510-523, 2014. https://doi.org/10.15837/ijccc.2014.4.228
  21. Falcone R, Castelfranchi C, "Social trust: A cognitive approach," Trust and deception in virtual societies; Springer, pp. 55-90, 2001.
  22. Granovetter M, "Economic action and social structure: The problem of embeddedness," American journal of sociology, vol. 91, no. 3, pp. 481-510, 1985. https://doi.org/10.1086/228311
  23. Hosmer L T, "Trust: The connecting link between organizational theory and philosophical ethics," Academy of Management Review, vol. 20, no. 2, pp. 379-403, 1995. https://doi.org/10.5465/amr.1995.9507312923
  24. Wei Z, "A Novel Trust Model Based on Recommendation for E-commere," in Proc. of the 2007 International Conference On Service Systems and Service Management, pp. 1-4, June 09-11, 2007.
  25. Ries S, Kangasharju J, Muhlhauser M, "A classification of trust systems," in Proc. of the OTM Confederated International Conferences on the Move to Meaningful Internet Systems, pp. 894-903, October 29 - November 3, 2006.
  26. Yuan W, Shu L, Chao H C, Guan D, Lee Y K, Lee S, "ITARS: trust-aware recommender system using implicit trust networks," IET Communications, vol. 4, no. 14, pp. 1709-1721, 2010. https://doi.org/10.1049/iet-com.2009.0733
  27. Salakhutdinov R, Mnih A, "Probabilistic Matrix Factorization," Advances in neural information processing systems, vol. 20, no. 1, pp. 1257-1264, 2008.
  28. Dueck D, Frey B, Dueck D, Frey B J, Probabilistic sparse matrix factorization: University of Toronto Report, 2004.
  29. Wang Z, Sun L, Zhu W, Yang S, Li H, Wu D, "Joint social and content recommendation for user-generated videos in online social network," IEEE Transactions on Multimedia, vol. 15, no. 3, pp. 698-709, 2013. https://doi.org/10.1109/TMM.2012.2237022
  30. Meng XW, Liu SD, Zhang YJ, Hu X, "Research on social recommender systems (in Chinese)," Ruan Jian Xue Bao/Journal of Software, vol. 26, no. 6, pp. 1356-1372, 2015.
  31. Yu L, Pan R, Li Z, "Adaptive social similarities for recommender systems," in Proc. of the fifth ACM conference on Recommender systems, pp. 257-260, October 23-27, 2011.
  32. Liu F, Lee H J, "Use of social network information to enhance collaborative filtering performance," Expert Systems with Applications, vol. 37, no. 7, pp. 4772-4778, 2010. https://doi.org/10.1016/j.eswa.2009.12.061
  33. Tang J, Hu X, Liu H, "Social recommendation: a review," Social Network Analysis and Mining, vol. 3, no. 4, pp. 1113-1133, 2013. https://doi.org/10.1007/s13278-013-0141-9
  34. Yang X, Guo Y, Liu Y, Steck H, "A survey of collaborative filtering based social recommender systems," Computer Communications, vol. 41, pp. 1-10, 2014. https://doi.org/10.1016/j.comcom.2013.06.009
  35. Ulusoy O, Tansel A U, Arkun E, "Recommendation and Search in Social Networks," Springer, 2015.
  36. Ma H, Yang H, Lyu M R, King I, "SoRec: social recommendation using probabilistic matrix factorization," in Proc. of the 17th ACM conference on Information and knowledge management, pp. 931-940, October 26-30, 2008.
  37. Gunawardana A, Shani G, "Evaluating recommender systems," Recommender Systems Handbook; Springer, pp. 265-308, 2015.