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Soft Computing

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19.10.2020 | Methodologies and Application

Circle-based Group Recommendation in Social Networks

verfasst von: Nirmal Choudhary, Sonajharia Minz, K. K. Bharadwaj

Erschienen in: Soft Computing | Ausgabe 22/2021

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Abstract

A large amount of data available on Web has proven to be an immense resource for innovative recommender system (RS) techniques and concepts. The traditional recommender system intended to provide recommendations for a single user. However, in certain domains the recommendation is required for a group of users. As to provide better recommendations for a group of users, we leverage the concept of circles in a network. In this work, we use the genetic algorithm (GA) K_Means clustering algorithm to generate social circles in a network. Then, we compute the status of each user in these overlapping circles. Finally, a circle-based group recommendation approach is used to generate the final group recommendation. The results obtained on the Epinions dataset validate the eminence of the proposed model over traditional approaches of group recommendation.

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http://www.trustlet.org/downloaded_epinions.html.

Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans Knowl Data Eng 6:734–749CrossRef

Agarwal V, Bharadwaj KK (2015) Predicting the dynamics of social circles in ego networks using pattern analysis and GA K-means clustering. Wiley Interdiscip Rev Data Min Knowl Discov 5(3):113–141CrossRef

Ardissono L, Goy A, Petrone G, Segnan M, Torasso P (2003) Intrigue: personalized recommendation of tourist attractions for desktop and hand held devices. Appl Artif Intell 17(8–9):687–714CrossRef

Baltrunas L, Makcinskas T, Ricci F (2010) Group recommendations with rank aggregation and collaborative filtering. In: Proceedings of the fourth ACM conference on Recommender systems, pp 119–126. ACM

Baskin JP, Krishnamurthi S (2009) Preference aggregation in group recommender systems for committee decision-making. In: Proceedings of the third ACM conference on Recommender systems, pp 337–340. ACM

Boratto L, Carta S (2010) State-of-the-art in group recommendation and new approaches for automatic identification of groups. In: Information retrieval and mining in distributed environments, pp 1–20. Berlin Heidelberg: Springer

Choudhary N, Bharadwaj KK (2018) Evolutionary learning approach to multi-agent negotiation for group recommender systems. Multimedia Tools Appl 1–23

Choudhary N, Bharadwaj KK (2019) Leveraging trust behaviour of users for group recommender systems in social networks. In: Integrated Intelligent Computing, Communication and Security, pp 41–47. Springer, Singapore

Christensen I, Schiaffino S, Armentano M (2016) Social group recommendation in the tourism domain. Journal of Intelligent Information Systems, pp 1–23

Crossen A, Budzik J, Hammond KJ (2002). Flytrap: intelligent group music recommendation. In: Proceedings of the 7th international conference on Intelligent user interfaces, pp 184–185. ACM

Dara S, Chowdary CR, Kumar C (2019) A survey on group recommender systems. J Intell Inf Syst 1–25

Eiben AE, Smith JE (2015) Introduction to evolutionary computing. Springer

Felfernig A, Boratto L, Stettinger M, Tkalčič M (2018) Evaluating group recommender systems. In: Group Recommender Systems, pp 59–71. Springer, Cham

Girdhar N, Bharadwaj KK (2019) Social status computation for nodes of overlapping communities in directed signed social networks. In: Integrated Intelligent Computing, Communication and Security, pp 49–57. Springer, Singapore

Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley Publishing Company Inc, BostonMATH

Jameson A (2004) More than the sum of its members: challenges for group recommender systems. In: Proceedings of the working conference on Advanced visual interfaces, pp. 48–54. ACM

Jameson A, Smyth B (2007) Recommendation to groups. In: The adaptive web, pp 596–627. Berlin Heidelberg: Springer

Xu B, Deng L, Jia, Y, Zhou B, Han Y (2013) Social circle analysis on ego-network based on context frequent pattern mining. In: Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service, pp 139–144. ACM

Kant V, Bharadwaj KK (2012) Enhancing recommendation quality of content-based filtering through collaborative predictions and fuzzy similarity measures. Procedia Eng 38:939–944CrossRef

Kim KJ, Ahn H (2008) A recommender system using GA K-means clustering in an online shopping market. Expert Syst Appl 34(2):1200–1209CrossRef

Kim JK, Kim HK, Oh HY, Ryu YU (2010) A group recommendation system for online communities. Int J Inf Manage 30(3):212–219CrossRef

Leskovec J, Huttenlocher D, Kleinberg J (2010) Signed networks in social media. In: Proceedings of the SIGCHI conference on human factors in computing systems, pp 1361–1370. ACM

Lieberman H, Van Dyke N, Vivacqua A (1999) Let’s browse: a collaborative browsing agent. Knowl-Based Syst 12(8):427–431CrossRef

Liu T, Qin H (2016) Detecting and tagging users’ social circles in social media. Multimedia Syst 22(4):423–431CrossRef

MacLean D, Hangal S, Teh SK, Lam MS, Heer J (2011) Groups without tears: mining social topologies from email. In: Proceedings of the 16th international conference on Intelligent user interfaces, pp 83–92

Massa P, Avesani P (2006) Trust-aware bootstrapping of recommender systems. In: ECAI workshop on recommender systems, pp 29–33

Masthoff J (2004) Group modeling: Selecting a sequence of television items to suit a group of viewers. In: Personalized digital television, pp 93–141. Springer, Dordrecht

McAuley J, Leskovec J (2014) Discovering social circles in ego networks. ACM Trans Knowl Discov Data (TKDD) 8(1):4

McCarthy JF (2002) Pocket restaurant finder: A situated recommender system for groups. In: Workshop on Mobile Ad-Hoc Communication at the 2002 ACM Conference on Human Factors in Computer Systems, p 8

McCarthy JF, Anagnost TD (1998) MusicFX: an arbiter of group preferences for computer supported collaborative workouts. In: Proceedings of the 1998 ACM conference on Computer supported cooperative work, pp 363–372. ACM

McCarthy K, McGinty L, Smyth B, Salamó M (2006) The needs of the many: a case-based group recommender system. In: European Conference on Case-Based Reasoning, pp 196–210. Springer, Berlin, Heidelberg

O’connor M, Cosley D, Konstan JA, Riedl J (2001) PolyLens: a recommender system for groups of users. In: ECSCW 2001, pp 199–218. Netherlands: Springer

Palla G, Derényi I, Farkas I, Vicsek T (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature 435(7043):814CrossRef

Qi GJ, Aggarwal CC, Huang T (2012) Community detection with edge content in social media networks. In: 2012 IEEE 28th International Conference on Data Engineering, pp 534–545. IEEE

Quijano-Sanchez L, Recio-Garcia JA, Diaz-Agudo B, Jimenez-Diaz G (2013) Social factors in group recommender systems. ACM Trans Intell Syst Technol (TIST) 4(1):8

Recio-Garcia JA, Jimenez-Diaz G, Sanchez-Ruiz AA, Diaz-Agudo B (2009) Personality aware recommendations to groups. In: Proceedings of the third ACM conference on Recommender systems, pp 325–328. ACM

Resnick P, Varian HR (1997) Recommender systems. Commun ACM 40(3):56–58CrossRef

Ricci F, Cavada D, Nguyen QN (2002) Integrating travel planning and on-tour support in a case-based recommender system. In: Proceedings of the Workshop on Mobile Tourism Systems, pp 11–16

Sahebi S, Cohen WW (1997) Community-based recommendations: a solution to the cold start problem. In: Proceedings of WOODSTOCK’97

Sinha RR, Swearingen K (2001) Comparing recommendations made by online systems and friends. In: DELOS

Symeonidis P, Tiakas E (2014) Transitive node similarity: predicting and recommending links in signed social networks. World Wide Web 17(4):743–776CrossRef

Villavicencio C, Schiaffino S, Diaz-Pace JA, Monteserin A, Demazeau Y, Adam C (2016) A MAS approach for group recommendation based on negotiation techniques. In: International Conference on Practical Applications of Agents and Multi-Agent Systems, pp 219–231. Springer, Cham

Yang X, Steck H, Liu Y (2012) Circle-based recommendation in online social networks. In: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, pp 1267–1275. ACM

Yu Z, Zhou X, Hao Y, Gu J (2006) TV program recommendation for multiple viewers based on user profile merging. User Model User-Adap Inter 16(1):63–82CrossRef

Titel: Circle-based Group Recommendation in Social Networks
verfasst von: Nirmal Choudhary
Sonajharia Minz
K. K. Bharadwaj
Publikationsdatum: 19.10.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 22/2021
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-020-05356-y

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