{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T16:46:33Z","timestamp":1780505193463,"version":"3.54.1"},"reference-count":38,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T00:00:00Z","timestamp":1677110400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Recommender systems are becoming an integral part of routine life, as they are extensively used in daily decision-making processes such as online shopping for products or services, job references, matchmaking for marriage purposes, and many others. However, these recommender systems are lacking in producing quality recommendations owing to sparsity issues. Keeping this in mind, the present study introduces a hybrid recommendation model for recommending music artists to users which is hierarchical Bayesian in nature, known as Relational Collaborative Topic Regression with Social Matrix Factorization (RCTR\u2013SMF). This model makes use of a lot of auxiliary domain knowledge and provides seamless integration of Social Matrix Factorization and Link Probability Functions into Collaborative Topic Regression-based recommender systems to attain better prediction accuracy. Here, the main emphasis is on examining the effectiveness of unified information related to social networking and an item-relational network structure in addition to item content and user-item interactions to make predictions for user ratings. RCTR\u2013SMF addresses the sparsity problem by utilizing additional domain knowledge, and it can address the cold-start problem in the case that there is hardly any rating information available. Furthermore, this article exhibits the proposed model performance on a large real-world social media dataset. The proposed model provides a recall of 57% and demonstrates its superiority over other state-of-the-art recommendation algorithms.<\/jats:p>","DOI":"10.3390\/s23052495","type":"journal-article","created":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T02:03:26Z","timestamp":1677204206000},"page":"2495","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Hybrid Recommendation Network Model with a Synthesis of Social Matrix Factorization and Link Probability Functions"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5442-4077","authenticated-orcid":false,"given":"Balraj","family":"Kumar","sequence":"first","affiliation":[{"name":"School of Computer Application, Lovely Professional University, Phagwara 144411, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neeraj","family":"Sharma","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Punjabi University, Patiala 147002, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3400-3504","authenticated-orcid":false,"given":"Bhisham","family":"Sharma","sequence":"additional","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9504-2275","authenticated-orcid":false,"given":"Norbert","family":"Herencsar","sequence":"additional","affiliation":[{"name":"Department of Telecommunications, Faculty of Electrical and Communication Engineering, Brno University of Technology, Technicka 12, 616 00 Brno, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9851-4103","authenticated-orcid":false,"given":"Gautam","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, Brandon University, Brandon, MB R7A 6A9, Canada"},{"name":"Department of Computer Science and Mathematics, Lebanese American University, Beirut 1102, Lebanon"},{"name":"Research Centre for Interneural Computing, China Medical University, Taichung 40402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,23]]},"reference":[{"key":"ref_1","unstructured":"Gupta, S., and Mishra, A. 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