Abstract
Online social networking has become a part of our everyday lives, and one of the popular online social network (SN) sites on the Internet is Facebook, where users communicate with their friends, join to groups, create groups, play games, and make friends around the world. Also, the vast number of groups are created for different causes and beliefs. However, overwhelming number of groups in one category causes difficulties for users to select a right group to join. To solve this problem, we introduce group recommendation system (GRS) using combination of hierarchical clustering technique and decision tree. We believe that Facebook SN groups can be identified based on their members’ profiles. Number of experiment results showed that GRS can make 73% accurate recommendation.
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References
Adamic, L.A., Buyukkokten, O., Adar, E.: A social network caught in the web. First Monday, vol. 8 (2003)
Backstrom, L., Huttenlocher, D.P., Kleinberg, J.M., Lan, X.: Group formation in large social networks: Membership, growth, and evolution. In: KDD, pp. 44–54 (2006)
Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees. Chapman & Hall, New York (1984)
Chickering, D.M., Heckerman, D.: A decision theoretic approach to targeted advertising. In: UAI, pp. 82–88 (2000)
Domingos, P., Richardson, M.: Mining the network value of customers. In: KDD, pp. 57–66 (2001)
Flake, G.W., Lawrence, S., Giles, C.L., Coetzee, F.: Self-organization and identification of web communities. IEEE Computer 35(3), 66–71 (2002)
Flake, G.W., Tarjan, R.E., Tsioutsiouliklis, K.: Graph clustering and minimum cut trees. Internet Mathematics 1(4), 385–408 (2004)
Girvan, M., Newman, M.: Community structure in social and biological networks. PNAS 99(12), 7821–7826 (2002)
Hoff, P.D., Raftery, A.E., Handcock, M.S.: Latent space approaches to social network analysis. Journal of the American Statistical Association 97(460), 1090–1098 (2002)
Hopcroft, J.E., Khan, O., Kulis, B., Selman, B.: Natural communities in large linked networks. In: KDD, pp. 541–546 (2003)
Liben-Nowell, D., Novak, J., Kumar, R., Raghavan, P., Tomkins, A.: Geographic routing in social networks. PNAS 102(33), 11623–11628 (2005)
Romesburg, H.C.: Cluster analysis for researchers. Lulu Press, North Carolina (2004)
Viegas, F.B., Smith, M.A.: Newsgroup crowds and authorlines: Visualizing the activity of individuals in conversational cyberspaces. In: HICSS (2004)
Wellman, B., Boase, J., Chen, W.: The networked nature of cummunity. IT&Society 1(1), 151–165 (2002)
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Baatarjav, EA., Phithakkitnukoon, S., Dantu, R. (2008). Group Recommendation System for Facebook. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2008 Workshops. OTM 2008. Lecture Notes in Computer Science, vol 5333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88875-8_41
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DOI: https://doi.org/10.1007/978-3-540-88875-8_41
Publisher Name: Springer, Berlin, Heidelberg
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