Abstract
Information collected from the social network is recently used to improve a performance of recommender systems to an individual user or a group. During selecting the items among the group members, the relationships (e.g., position, dependency, and the strength of the social ties) often has an important role than the individual preference in the group. Hence, we propose a novel recommendation method based on social affinity between two users. This recommendation method consists of (i) the similarity calculation between movies based on weighted feature, (ii) the generation of initial affinity network graph, and (iii) the computation of user’s affinity to group based on the graph. Experimental results on synthetic dataset show that our proposed method can discover social affinities efficiently.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
IMDB, http://www.imdb.com
- 2.
NAVER MOVIE, http://movie.naver.com/
- 3.
Facebook, https://www.facebook.com/
References
Yang, X., Guo, Y., Liu, Y., Steck, H.: A survey of collaborative filtering based social recommender systems. Comput. Commun. 41, 1–10 (2014)
Yang, X., Steck, H., Liu, Y.: Circle-based recommendation in online social networks. In: Yang, Q., Agarwal, D., Pei, J., (eds.) KDD, pp. 1267–1275. ACM (2012)
Ma, H., Yang, H., Lyu, M.R., King, I.: Sorec: social recommendation using probabilistic matrix factorization. In: Shanahan, J.G., Amer-Yahia, S., Manolescu, I., Zhang, Y., Evans, D.A., Kolcz, A., Choi, K.S., Chowdhury, A., (eds.) CIKM, pp. 931–940. ACM (2008)
Jamali, M., Ester, M.: A matrix factorization technique with trust propagation for recommendation in social networks. In: Amatriain, X., Torrens, M., Resnick, P., Zanker, M., (eds.) RecSys, pp. 135–142. ACM (2010)
Masthoff, J.: Group recommender systems: combining individual models. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 677–702. Springer, US (2011)
Masthoff, J.: Group modeling: selecting a sequence of television items to suit a group of viewers. User Model. User-Adapt. Inter. 14(1), 37–85 (2004)
Amer-Yahia, S., Roy, S.B., Chawla, A., Das, G., Yu, C.: Group recommendation: semantics and efficiency. PVLDB 2(1), 754–765 (2009)
Kim, J.K., Kim, H.K., Oh, H.Y., Ryu, Y.U.: A group recommendation system for online communities. Int. J. Inf. Manage. 30(3), 212–219 (2010)
Sánchez, L.Q., Recio-GarcÃa, J.A., DÃaz-Agudo, B., Jiménez-DÃaz, G.: Social factors in group recommender systems. ACM TIST 4(1), 8 (2013)
Debnath, S., Ganguly, N., Mitra, P.: Feature weighting in content based recommendation system using social network analysis. In: Huai, J., Chen, R., Hon, H.W., Liu, Y., Ma, W.Y., Tomkins, A., Zhang, X., (eds.) WWW, pp. 1041–1042. ACM (2008)
Wikipedia: Tf-idf. https://en.wikipedia.org/wiki/Tf
He, J., Chu, W.W.: A social network-based recommender system (SNRS). In: Memon, N., Xu, J.J., Hicks, D.L., Chen, H. (eds.) Data Mining for Social Network Data. Annals of Information Systems, vol. 12, pp. 47–74. Springer, US (2010)
Acknowledgement
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2015-H8501-15-1018) supervised by the IITP (Institute for Information&communications Technology Promotion). Also, this work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A2A2A05007154). Also, this research was supported by SW Master’s course of hiring contract Program grant funded by the Ministry of Science, ICT and Future Planning (H0116-15-1013).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Hong, M., Jung, J.J., Lee, M. (2016). Social Affinity-Based Group Recommender System. In: Vinh, P., Alagar, V. (eds) Context-Aware Systems and Applications. ICCASA 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 165. Springer, Cham. https://doi.org/10.1007/978-3-319-29236-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-29236-6_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-29235-9
Online ISBN: 978-3-319-29236-6
eBook Packages: Computer ScienceComputer Science (R0)