Recommender Systems for Social Networks: A Short Review

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Abstract

Since the 1990s, recommendation systems have been the subject of numerous studies. A recommender system is a software tool that assists users in the choice-making process by recommending items similar to their preferences and interests. However, in the age of the internet and social networking platforms, it is becoming more and more complex to provide the appropriate items for users due to the information overload problem. Hence, the introduction of a novel type of RS called "social recommender systems", an approach that employs social data to generate precise recommendations and surpass the classic recommender system's limitations. This article provides a brief overview of social recommender systems and their various methods.

References

David Goldberg, David Nichols, Brian M. Oki, and Douglas Terry. 1992. Using collaborative filtering to weave an information tapestry. Commun. ACM 35 (1992), 61–70. Issue 12.

Mark Claypool, Anuja Gokhale, Tim Miranda, Paul Murnikov, Dmitry Netes, and Matthew Sartin. 1999. Combing Content-Based and Collaborative Filters. (1999).

Chuan Shi, Yitong Li, Jiawei Zhang, Yizhou Sun, and Philip S. Yu. 2016. A Survey of Heterogeneous Information Network analysis. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 29, 1 (2016), 17–37.

Jyoti Shokeen and Chhavi Rana. 2020. Social recommender systems: techniques, domains,metrics, datasets and future scope. Journal of Intelligent Information Systems 54, 2 (2020), 1–35.

Jiliang Tang, Xia Hu, and Huan Liu. 2013. Social recommendation: a review. Social Network Analysis and Mining 3, 4 (2013), 1113–1133.

Macedo AQ, Marinho LB, and Santos RL. 2015. Context-aware event recommendation in event-based social networks. Proceedings of the 9th ACM conference on recommender systems, ACM (2015), 123–130.

Mohamad Arafeh, Paolo Ceravolo, Azzam Mourad, Ernesto Damiani, and Emanuele Bellini. 2021. Ontology based recommender system using social network data. Future Generation Computer Systems 115 (2021), 769–779.

Bo Chen, Yue Ding, Xin Xin, Yunzhe Li, Yule Wang, Yunzhe Li, and Dong Wang. 2021. AIRec: Attentive intersection model for tag-aware recommendation. Neurocomputing 421 (2021), 105–114.

Jyoti Shokeen and Chhavi Rana. 2020. A study on features of social recommender systems. Artificial Intelligence Review 53, 3 (2020).

Fangquan Zhen, Zhi Zhang, and Haichuan Lu. 2018. A review of social recommendation. 13th IEEE Conference on Industrial Electronics and Applications (ICIEA) (2018), 537–542. https://doi.org/10.1109/ICIEA.2018.839777.

Magdalini Eirinaki, Jerry Gao, Iraklis Varlamis, and Konstantinos Tserpes. 2018. Recommender Systems for Large-Scale Social Networks: A review of challenges and solutions. Future Generation Computer Systems 78 (2018), 413–418. https://doi.org/10.1016/j.future.2017.09.015

nitha Anandhan, Liyana Shuib, Maizatul Akmar Ismail, and Ghulam Mujtaba. 2018. Social media recommender systems: review and open research issues. IEEE Access 6 (2018), 15608 – 15628. https://doi.org/10.1109/ACCESS.2018.2810062

Jyoti Shokeen and Chhavi Rana. 2018. A review of the dynamics of social recommender systems. International Journal of Web Engineering and Technology 13, 3 (2018), 255–276. https://doi.org/10.1504/IJWET.2018.10016164

Mattia G. Campana and Franca Delmastro. 2017. Recommender systems for online and mobile social networks: A survey. Online Social Networks and Media 3–4 (2017), 75–97. https://doi.org/10.1016/j.osnem.2017.10.005

Revathy Vr and Anitha S. Pillai. 2017. Classification and application of social recommender systems. Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) (2017), 719–729. https: //doi.org/

Guandong Xu, Zhiang Wu, Yanchun Zhangand, and Jie Cao. 2015. Social networking meets recommender systems: survey. International Journal of Social Network Mining 2, 1 (2015), 64 – 100. https://doi.org/10.1504/IJSNM.2015.069773

Xiwang Yang, Yang Guo, Yong Liu, and Harald Steck. 2013. A survey of collaborative filtering based social recommender systems. Computer Communications 41 (2013), 1–10. https://doi.org/10.1016/j.comcom.2013.06.009

Mohammad Shabaz and Urvashi Garg. 2021. Shabaz–Urvashi Link Prediction (SULP): A Novel Approach to Predict Future Friends in a Social Network. Journal of Creative Communications 16, 1 (2021), 27–44.

Shweta Soni and Pratiksha Singhai. 2020. Friend Recommendation System Using machine learning method. International Journal of Scientific Research Engineering Trends 6, 5 (2020).

Jian-Ping Mei, Han Yu, Chunyan Miao, and Zhiqi Shen. 2017. A social influence-based trust model for recommender systems. Intelligent Data Analysis 21 (2017), 263–277. Issue 2.

Zafarani R and Liu H. 2013. Connecting users across social media sites: a behavioral-modeling approach. Proceedings of the 19th ACM SIGKDD international conference on knowledge discovery and data mining, ACM (2013), 41–49.

Faezeh Sadat Gohari and Mohammad Jafar Tarokh. 2016. A New Hybrid Collaborative Recommender using semantic technology and demographic data. International Journal of Information and Communication Technology Research 8, 2 (2016), 51–61.

Shaghayegh Sahebi and William W Cohen. 2011. Community-Based Recommendations: a Solution to the Cold Start Problem. Workshop on Recommender Systems and the Social Web (RSWEB) held in Conjunction with ACM RecSys (2011).

Maryam Fatemi and Laurissa Tokarchuk. 2013. A community based social recommender system for individuals and groups. 2013 International Conference on Social Computing (2013).

Sassi IB, Mellouli S, and Yahia SB. 2017. Context-aware recommender systems in mobile environment: On the road of future research. Inform Syst 72 (2017), 27–61

Adomavicius G and Tuzhilin A. 2011. Recommender systems handbook. Springer, Boston, Chapter Context-aware recommender systems, 217–253.

Leily Sheugh and Sasan H. Alizadeh. 2015. Merging Similarity and Trust Based Social Networks to Enhance the Accuracy of Trust-Aware Recommender Systems. Journal of Computer Robotics 8, 2 (2015), 43–51.

Sajad Ahmadian, Majid Meghdadi, and Mohsen Afsharchi. 2018. A social recommendation method based on an adaptive neighbor selection mechanism. Information Processing and Management 54, 4 (2018), 707–725.

Tinghuai MA, Jinjuan ZHOU, Meili TANG, Yuan TIAN, Abdullah AL-DHELAAN, Mznah AL-RODHAAN, and Sungyoung LEE. 2015. Social network and tag sources based augmenting collaborative recommender system. IEICE Trans Inform Syst 94, 4 (2015), 902–910.

Arnaboldi V, Campana MG, Delmastro F, and Pagani E. 2016. PLIERS: a popularity-based recommender system for content dissemination in online social networks. Proceedings of the 31st annual ACM symposium on applied computing (2016), 671–673.

Hashem Parvin, Parham Moradi, and Shahrokh Esmaeili. 2019. TCFACO: Trust-aware collaborative filtering method based on ant colony optimization.Expert Systems With Applications 118 (2019), 152–168.

Jyoti Shokeen and Chhavi Rana. 2021. A trust and semantic based approach for social recommendation. Journal of Ambient Intelligence and Humanized Computing 12, 11 (2021), 10289–10303.

Sonal Linda, Sonajharia Minz, and K.K. Bharadwaj. 2020. Effective Context-Aware Recommendations Based on Context Weighting Using Genetic Algorithm and Alleviating Data Sparsity. Applied Artificial Intelligence 34, 10 (2020), 730–753.

Yunhe Wei, Huifang Ma, and Ruoyi Zhang. 2022. Social influence-based personal latent factors learning for effective recommendation. Advances in Computational Intelligence 2, 5 (2022).

Punam Bedi Chhavi Sharma. 2017. CCFRS – Community based Collaborative Filtering Recommender System. Journal of Intelligent Fuzzy Systems 32, 4 (2017), 2987–2995.

CHang Su, Zongchao Hu, and Xianzhong Xie. 2020. Heterogeneous Social Recommendation Model with Network Embedding. IEEE Access 8 (2020).

Guafang Ma, Yuexuan Wang, Xiaolin Zhang, and Menghan Wang. 2018. Leveraging Transitive Trust relations to improve Cross-domain recommendation. IEEE Access 6 (2018), 38012–38025.

Chong Chen, Weizhi Ma, Min Zhang, Zhaowei Wang, Xiuqiang He, Chenyang Wang, Yiqun Liu, and Shaoping Ma. 2021. Graph Heterogeneous Multi-Relational Recommendation. The Thirty-Fifth AAAI Conference on Artificial Intelligence (2021).

Maria Stratigi, Evaggelia Pitoura, and Kostas Stefanidis. 2022. SQUIRREL: A framework for sequential group recommendations through reinforcement learning. Information Systems 112 (2022).

Hanfei Wang, Yuan Zuo, Hong Li, and Junjie Wu. 2021. Cross-domain recommendation with user personality. Knowledge-Based Systems 213 (2021).

Kosaraju Naren Kumar and Kanakamedala Vineela. 2020. Friend recommendation using graph mining on social media. International Journal of Engineering Technology and Management Sciences 4, 5 (2020).

Ashkan Yeganeh Zaremarjal and Derya Yiltas-Kaplan. 2021. Semantic Collaborative Filtering Recommender System Using CNNs. 8th International Conference on Electrical and Electronics Engineering (2021).