The Role of Trust to Enhance the Recommendation System Based on Social Network

Muhammed E Abd Alkhalec Tharwat, Deden Witarsyah Jacob, Mohd Farhan Md Fudzee, Shahreen Kasim, Azizul Azhar Ramli, Muharman Lubis

Abstract


Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is widely utilized to predict an item to the end-user based on his/her preferences primary. Recommendation systems applied in many areas mainly in commercial applications. This work aims to collect evidence of utilizing social network information between users to enhance the quality of traditional recommendation system. It provides an overview of traditional and modern approaches used by RSs such as collaborative filter (CF) approach, content-based (CB) approach, and hybrid filter approach. CF is one of the most famous traditional approaches in RSs, which is facing many limitations due to the lack of information available during a performance such as Cold start, Sparsity and Shilling attack. Additionally, this content focused on the role of incorporating a trust relationship from the social network to enhance the weaknesses of CF and achieve better quality in the recommendation process. Trust-aware Recommendation Systems (TaRSs) is a modern approach proposed to overcome the limitations of CF recommendation system in a social network. The trust relationship between users can boost and enhance CF limitations. Many researchers are focusing on trust in the recommendation system but fewer works are highlighting the role of trust in the recommendation system. In the end, limitations, and open issues of the current picture of the recommendation system come across. 


Keywords


recommendation system; recommender system; trust; distrust; social network.

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References


R. Francesco, R. Lior, and B. Shapira, Recommender system handbook. 2011.

X. Ma, H. Lu, Z. Gan, and J. Zeng, “An explicit trust and distrust clustering based collaborative filtering recommendation approach,†Electron. Commer. Res. Appl., vol. 25, pp. 29–39, 2017.

Y. Yu, Y. Gao, H. Wang, and R. Wang, “Joint user knowledge and matrix factorization for recommender systems,†World Wide Web, pp. 1–23, 2017.

Charu C. Aggarwal (auth.), Recommender Systems : The Textbook. IBM T.J. Watson Research Center Yorktown Heights, NY, USA: Springer International Publishing, 2016.

N. Polatidis and C. K. Georgiadis, “Recommender Systems:,†Int. J. E-entrepreneursh. Innov., vol. 4, no. 4, pp. 32–46, 2013.

F. O. Isinkaye, Y. O. Folajimi, and B. A. Ojokoh, “Recommendation systems: Principles, methods and evaluation,†Egypt. Informatics J., vol. 16, no. 3, pp. 261–273, 2015.

Z. Zhang, Y. Liu, Z. Jin, and R. Zhang, “Selecting influential and trustworthy neighbors for collaborative filtering recommender systems,†2017 IEEE 7th Annu. Comput. Commun. Work. Conf. CCWC 2017, no. 1, 2017.

A. Salah and M. Nadif, “Social regularized von Mises–Fisher mixture model for item recommendation,†Data Min. Knowl. Discov., vol. 31, no. 5, pp. 1218–1241, 2017.

H. M. Kim, B. Ghiasi, M. Spear, M. Laskowski, and J. Li, “Online serendipity: The case for curated recommender systems,†Bus. Horiz., vol. 60, no. 5, pp. 613–620, 2017.

N. S. Nizamkari, “A Graph-based Trust-enhanced Recommender System for Service Selection in IOT,†in International Conference on Inventive Systems and Control (ICISC-2017) A, 2017, pp. 1–5.

P. He, L. Yu, J. Li, and C. Wen, “CR-IIA : Collaborative Recommendation Algorithm Based on Implicit Item Associations,†2017.

B. Heitmann and C. Hayes, “Using Linked Data to Build Open , Collaborative Recommender Systems ∗,†AAAI Spring Symp. Linked Data Meets Artif. Intell., pp. 76–81, 2010.

P. Kefalas and Y. Manolopoulos, “A time-aware spatio-textual recommender system,†Expert Syst. Appl., vol. 78, pp. 396–406, 2017.

J. Lu, D. Wu, M. Mao, W. Wang, and G. Zhang, “Recommender system application developments: A survey,†Decis. Support Syst., vol. 74, pp. 12–32, 2015.

X. Su and T. M. Khoshgoftaar, “A Survey of Collaborative Filtering Techniques,†Adv. Artif. Intell., vol. 2009, no. Section 3, pp. 1–19, 2009.

C. Breese, J.S., Heckerman, D., Kadie, “Empirical Analysis of Predictive Algorithm for Collaborative Filtering,†in Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence, 1998, no. November, pp. 43–52.

M. Eirinaki, J. Gao, I. Varlamis, and K. Tserpes, “Recommender Systems for Large-Scale Social Networks: A review of challenges and solutions,†Futur. Gener. Comput. Syst., vol. 78, pp. 413–418, 2018.

Z. Yu, C. Chen, X. Zheng, W. Ding, and D. Chen, “Context-Aware Trust Aided Recommendation via Ontology and Gaussian Mixture Model in Big Data Environment,†in 2014 International Conference on Service Sciences, 2014, pp. 85–90.

Y. Koren, R. Bell, and C. Volinsky, “Matrix factorization techniques for recommender systems.,†Computer., vol. 42, pp. 30–37, 2009.

Y. X. Yuqing Shi, Huan Zhao, “A New Hybrid Collaborative Filtering Algorithm with Combination of Trust,†in 3rd International Conference on Information and Communication Technology for Education (ICTE 2016), 2016.

Q. Li, J. Wang, Y. P. Chen, and Z. Lin, “User comments for news recommendation in forum-based social media,†Inf. Sci. (Ny)., vol. 180, no. 24, pp. 4929–4939, 2010.

H. Wang and W. J. Li, “Relational collaborative topic regression for recommender systems,†IEEE Trans. Knowl. Data Eng., vol. 27, no. 5, pp. 1343–1355, 2015.

C. L. Sanchez Bocanegra, J. L. Sevillano Ramos, C. Rizo, A. Civit, and L. Fernandez-Luque, “HealthRecSys: A semantic content-based recommender system to complement health videos,†BMC Med. Inform. Decis. Mak., vol. 17, no. 1, pp. 1–10, 2017.

Z. Sun et al., “Recommender systems based on social networks,†J. Syst. Softw., vol. 99, pp. 109–119, 2015.

S. G. Lops P., de Gemmis M., “Content-based Recommender Systems: State of the Art and Trends,†in Recommender Systems Handbook, vol. 532, K. P. Ricci F., Rokach L., Shapira B., Ed. Boston, MA, 2011, pp. 73–105.

A. A. Kardan and M. Ebrahimi, “A novel approach to hybrid recommendation systems based on association rules mining for content recommendation in asynchronous discussion groups,†Inf. Sci. (Ny)., vol. 219, pp. 93–110, 2013.

M. J. Pazzani and D. Billsus, “Content-Based Recommendation Systems,†in The Adaptive Web. Lecture Notes in Computer Science, vol 4321, W. rusilovski, Peter, Kobsa, Alfred, Nejdl, Ed. Springer, Berlin, Heidelberg, 2007, pp. 325–341.

J. Salter and N. Antonopoulos, “CinemaScreen recommander agent: Combining collaborative and content-based filtering,†IEEE Intell. Syst., vol. 21, no. 1, pp. 35–41, 2006.

S. Sharma, A. Sharma, Y. Sharma, and M. Bhatia, “Recommender system using hybrid approach,†2016 Int. Conf. Comput. Commun. Autom., pp. 219–223, 2016.

N. Wang, Z. Chen, and X. Li, “Heterogeneous trust-aware recommender systems in social network,†in 2017 IEEE 2nd International Conference on Big Data Analysis, ICBDA 2017, 2017, pp. 767–771.

G. A. L. Bouneffouf D., Bouzeghoub A., “Risk-Aware Recommender Systems,†in International Conference on Neural Information Processing, 2013, vol. 8226, no. January, pp. 57–65.

J. Bobadilla, F. Ortega, A. Hernando, and A. Gutiérrez, “Recommender systems survey,†Knowledge-Based Syst., vol. 46, pp. 109–132, 2013.

R. Logesh and V. Subramaniyaswamy, “A Reliable Point of Interest Recommendation based on Trust Relevancy between Users,†Wirel. Pers. Commun., vol. 97, no. 2, pp. 2751–2780, 2017.

B. Yang, Y. Lei, J. Liu, and W. Li, “Social Collaborative Filtering by Trust,†Proc. Twenty-Third Int. Jt. Conf. Artif. Intell., p. 2747–2753., 2013.

C. Posse, “Key lessons learned building recommender systems for large-scale social networks,†Proc. 18th ACM SIGKDD Int. Conf. Knowl. Discov. data Min. - KDD ’12, p. 587, 2012.

F. Liu and H. J. Lee, “Use of social network information to enhance collaborative filtering performance,†Expert Syst. Appl., vol. 37, no. 7, pp. 4772–4778, 2010.

P. Massa and P. Avesani, “Trust-aware Recommender Systems,†in RecSys ’07 Proceedings of the 2007 ACM conference on Recommender systems, 2007, pp. 17–24.

M. Jamali and M. Ester, “TrustWalker: a random walk model for combining trust-based and item-based recommendation,†Proc. 15th ACM SIGKDD Int. Conf. Knowl. Discov. data Min., pp. 397–406, 2009.

X. L. Zheng, C. C. Chen, J. L. Hung, W. He, F. X. Hong, and Z. Lin, “A Hybrid Trust-Based Recommender System for Online Communities of Practice,†IEEE Trans. Learn. Technol., vol. 8, no. 4, pp. 345–356, 2015.

H. Ma, I. King, and M. R. Lyu, “Learning to recommend with social trust ensemble,†Proc. 32nd Int. ACM SIGIR Conf. Res. Dev. Inf. Retr. - SIGIR ’09, p. 203, 2009.

M. Jamali and M. Ester, “A matrix factorization technique with trust propagation for recommendation in social networks,†Proc. fourth ACM Conf. Recomm. Syst. - RecSys ’10, p. 135, 2010.

X. M. L. Gan, “Implicit trust and distrust prediction for recommender systems,†in Web Information Systems Engineering – WISE 2015, 2015, pp. 240–640.

R. Forsati, M. Mahdavi, M. Shamsfard, and M. Sarwat, “Matrix Factorization with Explicit Trust and Distrust Side Information for Improved Social Recommendation,†ACM Trans. Inf. Syst., vol. 32, no. 4, pp. 1–38, 2014.

G. Guo, J. Zhang, and N. Yorke-Smith, “Leveraging multiviews of trust and similarity to enhance clustering-based recommender systems,†Knowledge-Based Syst., vol. 74, pp. 14–27, 2015.

W. P. Lee and C. Y. Ma, “Enhancing collaborative recommendation performance by combining user preference and trust-distrust propagation in social networks,†Knowledge-Based Syst., vol. 106, pp. 125–134, 2016.

S. J. Akshi Kumar, Indu Bala, “A Comprehensive Study of TARS : Definition , metrics and advancements,†in 2017 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON), 2017, pp. 199–204.

N. Lankton, D. H. McKnight, and J. Tripp, “Technology, Humanness, and Trust: Rethinking Trust in Technology,†J. Assoc. Inf. Syst., vol. 16, no. 10, pp. 880–918, 2015.

W. Sherchan, S. Nepal, and C. Paris, “A survey of trust in social networks,†ACM Comput. Surv., vol. 45, no. 4, pp. 1–33, 2013.

P. Dumouchel, “Trust as an action,†Arch. Eur. Sociol., vol. 46, no. 3, pp. 417–428, 2005.

D. Artz and Y. Gil, “A survey of trust in computer science and the Semantic Web,†Web Semant., vol. 5, no. 2, pp. 58–71, 2007.

A. Jøsang, R. Ismail, and C. Boyd, “A survey of trust and reputation systems for online service provision,†Decis. Support Syst., vol. 43, pp. 618–644, 2007.

K. K. B. Vibhor Kant, “Fuzzy Computational Models of Trust and Distrust for Enhanced Recommendations,†Int. J. Intell. Syst., vol. 28, no. 4, pp. 332–365, 2013.

C. C. Chen, Y. H. Wan, M. C. Chung, and Y. C. Sun, “An effective recommendation method for cold start new users using trust and distrust networks,†Inf. Sci. (Ny)., vol. 224, pp. 19–36, 2013.

Y. Ruan and A. Durresi, “A survey of trust management systems for online social communities - Trust modeling, trust inference and attacks,†Knowledge-Based Syst., vol. 106, pp. 150–163, 2016.

F. S. Gohari, H. Haghighi, and F. S. Aliee, “A semantic-enhanced trust based recommender system using ant colony optimization,†Appl. Intell., vol. 46, no. 2, pp. 328–364, 2017.

Vibhor Kant and Kamal K. Bharadwaj, “Incorporating Fuzzy Trust in Collaborative Filtering Based Recommender Systems,†in Advances in User Modeling ,UMAP 2011Workshops Girona, Spain, July 11-15, 2011 Revised Selected Papers, 2011, pp. 433–440.

M. Taherpour, H. Shaken, and M. Mali, “Improvement of recommender systems using confidence-aware trust,†2014 Int. Congr. Technol. Commun. Knowledge, ICTCK 2014, no. Ictck, pp. 26–27, 2014.

A. M. Shabut and K. Dahal, “Social factors for data sparsity problem of trust models in MANETs,†in 2017 International Conference on Computing, Networking and Communications, ICNC 2017, 2017, pp. 876–880.

V. Faridani, M. Jalali, and M. V. Jahan, “Collaborative filtering-based recommender systems by effective trust,†Int. J. Data Sci. Anal., vol. 3, no. 4, pp. 297–307, 2017.

D. H. Alahmadi and X. J. Zeng, “Twitter-based recommender system to address cold-start: A genetic algorithm based trust modelling and probabilistic sentiment analysis,†in 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI), 2015, pp. 1045–1052.

S. S. Thanaphon Phukseng, “Calculating trust by considering user similarity and social trust for recommendation systems,†in 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Calculating, 2017, pp. 1–6.

S. Zahra, M. A. Ghazanfar, A. Khalid, M. A. Azam, U. Naeem, and A. Prugel-Bennett, “Novel centroid selection approaches for KMeans-clustering based recommender systems,†Inf. Sci. (Ny)., vol. 320, pp. 156–189, 2015.

N. P. Kumar and Z. Fan, “Hybrid user-item based collaborative filtering,†Procedia Comput. Sci., vol. 60, no. 1, pp. 1453–1461, 2015.

C. Li and K. He, “CBMR: An optimized MapReduce for item-based collaborative filtering recommendation algorithm with empirical analysis,†Concurr. Comput., vol. 29, no. 10, pp. 1–7, 2017.

N. Polatidis, C. K. Georgiadis, E. Pimenidis, and H. Mouratidis, “Privacy-preserving collaborative recommendations based on random perturbations,†Expert Syst. Appl., vol. 71, pp. 18–25, 2017.

S. Berkovsky, R. Taib, and D. Conway, “How to Recommend ? User Trust Factors in Movie Recommender Systems,†[IUI2017]Proceedings 22nd Int. Conf. Intell. User Interfaces, pp. 287–300, 2017.

L. Quijano-Sanchez, C. Sauer, J. A. Recio-Garcia, and B. Diaz-Agudo, “Make it personal: A social explanation system applied to group recommendations,†Expert Syst. Appl., vol. 76, pp. 36–48, 2017.

S. L. and K. K. Bharadwaj, “A Fuzzy Trust Enhanced Collaborative Filtering for Effective Context-Aware Recommender Systems,†in Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 1, 2016, vol. 1, pp. 227–237.

J. Wang, S. Zhang, X. Liu, Y. Jiang, and M. Zhang, “A novel collective matrix factorization model for recommendation with fine-grained social trust prediction,†Concurr. Comput. , vol. 29, no. 19, pp. 1–14, 2017.

L. Yu, L. Liu, and X. Li, “A hybrid collaborative filtering method for multiple-interests and multiple-content recommendation in E-Commerce,†Expert Syst. Appl., vol. 28, no. 1, pp. 67–77, 2005.

F. S. Gohari, H. Haghighi, and F. S. Aliee, “A semantic-enhanced trust based recommender system using ant colony optimization,†Appl. Intell., vol. 46, no. 2, pp. 328–364, 2017.

P. Massa and P. Avesani, “Trust-aware collaborative filtering for recommender systems,†in On the Move to Meaningful Internet Systems 2004: CoopIS, DOA, and ODBASE, 2004, vol. 3290, pp. 492–508.

P. Victor, C. Cornelis, M. De Cock, and A. M. Teredesai, “Key figure impact in trust-enhanced recommender systems,†AI Commun. AI Commun. - Recomm. Syst., vol. 21, no. 2–3, pp. 127–143, 2008.

J. O’Donovan and B. Smyth, “Trust in recommender systems,†in Proceedings of the 10th international conference on Intelligent user interfaces, 2005, pp. 167–174.

X. Zhou, Y. Xu, Y. Li, A. Josang, and C. Cox, “The state-of-the-art in personalized recommender systems for social networking,†Artif. Intell. Rev., vol. 37, no. 2, pp. 119–132, 2012.

M. Frikha, M. Mhiri, M. Zarai, and F. Gargouri, “Using TMT ontology in trust based medical tourism recommender system,†in Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, 2016.




DOI: http://dx.doi.org/10.18517/ijaseit.10.4.10883

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