Table of Contents Author Guidelines Submit a Manuscript
Wireless Communications and Mobile Computing
Volume 2018, Article ID 6709607, 11 pages
https://doi.org/10.1155/2018/6709607
Research Article

Group Recommendation Systems Based on External Social-Trust Networks

Kunming University of Science and Technology, Kunming 650051, China

Correspondence should be addressed to Lei Su; moc.liamtoh@14382s

Received 14 February 2018; Accepted 16 April 2018; Published 29 May 2018

Academic Editor: Huimin Lu

Copyright © 2018 Guang Fang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. Jameson and B. Smyth, “Recommendation to groups,” in Adaptive Web, pp. 596–627, 2007. View at Google Scholar
  2. A. Jameson, “More than the sum of its members: Challenges for group recommender systems,” in Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2004, pp. 48–54, ita, May 2004. View at Publisher · View at Google Scholar · View at Scopus
  3. M. Kompan and M. Bielikova, “Group recommendations: Survey and perspectives,” Computing and Informatics, vol. 33, no. 2, pp. 446–476, 2014. View at Google Scholar · View at Scopus
  4. L. Quijano-Sanchez, J. A. Recio-Garcia, and B. Diaz-Agudo, “Personality and Social Trust in Group Recommendations,” in Proceedings of the 2010 22nd International Conference on Tools with Artificial Intelligence (ICTAI), pp. 121–126, Arras, France, October 2010. View at Publisher · View at Google Scholar
  5. L. Quijano-Sanchez, J. A. Recio-Garcia, B. Diaz-Agudo, and G. Jimenez-Diaz, “Social factors in group recommender systems,” ACM Transactions on Intelligent Systems and Technology, vol. 4, no. 1, article no. 8, 2013. View at Publisher · View at Google Scholar · View at Scopus
  6. L. Quijano-Sánchez, B. Díaz-Agudo, and J. A. Recio-García, “Development of a group recommender application in a Social Network,” Knowledge-Based Systems, vol. 71, pp. 72–85, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Gartrell, X. Xing, Q. Lv et al., “Enhancing group recommendation by incorporating social relationship interactions,” in Proceedings of the 16th ACM International Conference on Supporting Group Work, GROUP'10, pp. 97–106, usa, November 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. L. Quijanosanchez, J. Reciogarcia, and B. Diazagudo, Group recommendation methods for social network environments, 2011.
  9. I. A. Christensen and S. Schiaffino, “Social influence in group recommender systems,” Online Information Review, vol. 38, no. 4, pp. 524–542, 2014. View at Publisher · View at Google Scholar · View at Scopus
  10. F. Supan, K. Takanori, F. Goonnapa et al., “Group modeling: Selecting a sequence of television items to suit a group of viewers,” User Modeling and User-Adapted Interaction, vol. 14, no. 1, pp. 37–85, 2004. View at Google Scholar
  11. F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, Eds., Recommender Systems Handbook, Springer, 2011. View at Publisher · View at Google Scholar
  12. F. Ortega, J. Bobadilla, A. Hernando, and A. Gutiérrez, “Incorporating group recommendations to recommender systems: Alternatives and performance,” Information Processing & Management, vol. 49, no. 4, pp. 895–901, 2013. View at Publisher · View at Google Scholar · View at Scopus
  13. N. A. Najjar and D. C. Wilson, “Differential neighborhood selection in memory-based group recommender systems,” in Proceedings of the 27th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2014, pp. 69–74, usa, May 2014. View at Scopus
  14. J. Kelleher and D. Bridge, An Accurate and Scalable Collaborative Recommender, Kluwer Academic Publishers, 2004.
  15. L. Baltrunas, T. Makcinskas, and F. Ricci, “Group recommendations with rank aggregation and collaborative filtering,” in Proceedings of the 4th ACM Recommender Systems Conference, RecSys 2010, pp. 119–126, esp, September 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. S. Berkovsky and J. Freyne, “Group-based recipe recommendations: analysis of data aggregation strategies,” in Proceedings of the 4th ACM Recommender Systems Conference (RecSys '10), pp. 111–118, Barcelona, Spain, September 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. G. Linden, B. Smith, and J. York, “Amazon.com recommendations: item-to-item collaborative filtering,” IEEE Internet Computing, vol. 7, no. 1, pp. 76–80, 2003. View at Publisher · View at Google Scholar · View at Scopus
  18. J. Ben Schafer, F. Dan, J. Herlocker, and S. Sen, Collaborative Filtering Recommender Systems, Springer, Berlin, Germany, 2007.
  19. B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, “Item-based collaborative filtering recommendation algorithms,” in Proceedings of the 10th International Conference on World Wide Web (WWW '01), pp. 285–295, 2001. View at Publisher · View at Google Scholar
  20. Y. Zhang, M. Chen, D. Huang, D. Wu, and Y. Li, “IDoctor: personalized and professionalized medical recommendations based on hybrid matrix factorization,” Future Generation Computer Systems, vol. 66, pp. 30–35, 2017. View at Publisher · View at Google Scholar · View at Scopus
  21. Y. Zhang, “GroRec: a group-centric intelligent recommender system integrating social, mobile and big data technologies,” IEEE Transactions on Services Computing, vol. 9, no. 5, pp. 786–795, 2016. View at Publisher · View at Google Scholar · View at Scopus
  22. Y. Zhang, Z. Tu, and Q. Wang, “TempoRec: Temporal-Topic Based Recommender for Social Network Services,” Mobile Networks and Applications, vol. 22, pp. 1182–1191, 2017. View at Publisher · View at Google Scholar · View at Scopus
  23. Y. Zhang, D. Zhang, M. M. Hassan, A. Alamri, and L. Peng, “CADRE: Cloud-Assisted Drug REcommendation Service for Online Pharmacies,” Mobile Networks and Applications, vol. 20, no. 3, pp. 348–355, 2015. View at Publisher · View at Google Scholar · View at Scopus
  24. J. F. McCarthy and T. D. Anagnost, “MUSICFX: an arbiter of group preferences for computer supported collaborative workouts,” in Proceedings of the 7th ACM Conference on Computer Supported Cooperative Work (CSCW '98), pp. 363–372, November 1998. View at Scopus
  25. A. Crossen, J. Budzik, and K. J. Hammond, “Flytrap: Intelligent group music recommendation,” in Proceedings of the 2002 International Conference on intelligent User Interfaces (IUI 02), pp. 184-185, usa, January 2002. View at Scopus
  26. C. Baccigalupo and E. Plaza, “A case-based song scheduler for group customised radio,” in Proceedings of the International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development, pp. 433–448, 2007.
  27. H. Lieberman, N. W. Van Dyke, and A. S. Vivacqua, “Let's Browse: a collaborative web browsing agent,” in Proceedings of the 1998 11th Annual ACM Symposium on User Interface Software and Technology, UIST-98, pp. 65–68, November 1998. View at Scopus
  28. K. McCarthy, M. Salamó, L. Coyle, L. McGinty, B. Smyth, and P. Nixon, “CATS: A synchronous approach to collaborative group recommendation,” in Proceedings of the FLAIRS 2006 - 19th International Florida Artificial Intelligence Research Society Conference, pp. 86–91, Melbourne Beach, Florida, USA, May 2006. View at Scopus
  29. L. Ardissono, A. Goy, G. Petrone, M. Segnan, and P. Torasso, “Intrigue: personalized recommendation of tourist attractions for desktop and hand held devices,” Applied Artificial Intelligence, vol. 17, no. 8-9, pp. 687–714, 2003. View at Publisher · View at Google Scholar · View at Scopus
  30. J. F. Mccarthy, Pocket restaurantfinder: A situated recommender system for groups, 2002.
  31. S. Shin, S.-J. Jang, and S.-P. Lee, “The user-group based recommendation for the diverse multimedia contents in the social network environments,” in Proceedings of the 9th International Conference on Dependable, Autonomic and Secure Computing, pp. 202–206, December 2011. View at Publisher · View at Google Scholar · View at Scopus
  32. J. K. Kim, H. K. Kim, H. Y. Oh, and Y. U. Ryu, “A group recommendation system for online communities,” International Journal of Information Management, vol. 30, no. 3, pp. 212–219, 2010. View at Publisher · View at Google Scholar · View at Scopus
  33. J. E. John, “Thomas-kilmann conflict mode instrument,” Group & Organization Management, vol. 1, no. 2, pp. 249–251, 1976. View at Google Scholar
  34. J. S. Dyer and R. K. Sarin, “Group preference aggregation rules based on strength of preference,” Management Science, vol. 25, no. 9, pp. 822–832 (1980), 1979. View at Publisher · View at Google Scholar · View at MathSciNet
  35. G. Guo, J. Zhang, and N. Yorke-Smith, “A novel bayesian similarity measure for recommender systems,” in Proceedings of the 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013, pp. 2619–2625, chn, August 2013. View at Scopus