{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T05:43:49Z","timestamp":1768887829945,"version":"3.49.0"},"reference-count":28,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,2,4]],"date-time":"2023-02-04T00:00:00Z","timestamp":1675468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>The Artificial Intelligence Recommender System has emerged as a significant research interest. It aims at helping users find things online by offering recommendations that closely fit their interests. Recommenders for research papers have appeared over the last decade to make it easier to find publications associated with the field of researchers\u2019 interests. However, due to several issues, such as copyright constraints, these methodologies assume that the recommended articles\u2019 contents are entirely openly accessible, which is not necessarily the case. This work demonstrates an efficient model, known as RPRSCA: Research Paper Recommendation System Using Effective Collaborative Approach, to address these uncertain systems for the recommendation of quality research papers. We make use of contextual metadata that are publicly available to gather hidden relationships between research papers in order to personalize recommendations by exploiting the advantages of collaborative filtering. The proposed system, RPRSCA, is unique and gives personalized recommendations irrespective of the research subject. Thus, a novel collaborative approach is proposed that provides better performance. Using a publicly available dataset, we found that our proposed method outperformed previous uncertain methods in terms of overall performance and the capacity to return relevant, valuable, and quality publications at the top of the recommendation list. Furthermore, our proposed strategy includes personalized suggestions and customer expertise, in addition to addressing multi-disciplinary concerns.<\/jats:p>","DOI":"10.3390\/systems11020081","type":"journal-article","created":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T05:29:05Z","timestamp":1675661345000},"page":"81","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["High-Performance Artificial Intelligence Recommendation of Quality Research Papers Using Effective Collaborative Approach"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1070-3212","authenticated-orcid":false,"given":"Vinoth Kumar","family":"Venkatesan","sequence":"first","affiliation":[{"name":"School of Information Technology and Engineering, VIT University, Vellore 632014, Tamil Nadu, India"}]},{"given":"Mahesh Thyluru","family":"Ramakrishna","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Faculty of Engineering and Technology, JAIN (Deemed-to-be University), Bangalore 562112, Karnataka, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7650-7383","authenticated-orcid":false,"given":"Anatoliy","family":"Batyuk","sequence":"additional","affiliation":[{"name":"Department of Automated Control Systems, Lviv Polytechnic National University, 79013 Lviv, Ukraine"}]},{"given":"Andrii","family":"Barna","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence, Lviv Polytechnic National University, 79013 Lviv, Ukraine"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3213-9747","authenticated-orcid":false,"given":"Bohdana","family":"Havrysh","sequence":"additional","affiliation":[{"name":"Department of Publishing Information Technologies, Lviv Polytechnic National University, 79013 Lviv, Ukraine"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,4]]},"reference":[{"key":"ref_1","first-page":"96","article-title":"An Ontological Framework for Research Paper recommendation","volume":"11","author":"Haruna","year":"2016","journal-title":"Int. J. Soft Comput."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/s00799-014-0122-2","article-title":"A comprehensive evaluation of scholarly paper recommendation using potential citation papers","volume":"16","author":"Sugiyama","year":"2015","journal-title":"Int. J. Digit. Libr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1695","DOI":"10.1109\/ACCESS.2015.2481320","article-title":"Context-Based Collaborative Filtering for Citation Recommendation","volume":"3","author":"Liu","year":"2015","journal-title":"IEEE Access"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"111484","DOI":"10.1016\/j.measurement.2022.111484","article-title":"An IoT based authentication system for therapeutic herbs measured by local descriptors using machine learning approach","volume":"200","author":"Roopashree","year":"2022","journal-title":"Measurement"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Beel, J., Langer, S., Genzmehr, M., and N\u00fcrnberger, A. (2013, January 22\u201326). Introducing Docear\u2019s research paper recommender system. Proceedings of the 13th ACM\/IEEE-CS Joint Conference on Digital Libraries, Indianapolis, IN, USA.","DOI":"10.1145\/2467696.2467786"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ramakrishna, M.T., Venkatesan, V.K., Izonin, I., Havryliuk, M., and Bhat, C.R. (2023). Homogeneous Adaboost Ensemble Machine Learning Algorithms with Reduced Entropy on Balanced Data. Entropy, 25.","DOI":"10.3390\/e25020245"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"McNee, S.M., Albert, I., Cosley, D., Gopalkrishnan, P., Lam, S.K., Rashid, A.M., Konstan, J.A., and Riedl, J. (2002, January 16\u201320). On the recommending of citations for research papers. Proceedings of the 2002 ACM Conference on Computer Supported Cooperative Work, New Orleans, LA, USA.","DOI":"10.1145\/587078.587096"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Vivek, V., Mahesh, T.R., Saravanan, C., and Kumar, K.V. (2022). A Novel Technique for User Decision Prediction and Assistance Using Machine Learning and NLP: A Mod-el to Transform the E-commerce System. InBig Data Management in Sensing, River Publishers.","DOI":"10.1201\/9781003337355-5"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Nascimento, C., Laender, A.H., da Silva, A.S., and Gon\u00e7alves, M.A. (2011, January 13\u201317). A source independent framework for research paper recommendation. Proceedings of the 11th Annual International ACM\/IEEE Joint Conference on Digital Libraries, Ottawa, ON, Canada.","DOI":"10.1145\/1998076.1998132"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1080\/08839514.2021.1881297","article-title":"Trust and Distrust based Cross-domain Recommender System","volume":"35","author":"Richa","year":"2021","journal-title":"Appl. Artif. Intell."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e0184516","DOI":"10.1371\/journal.pone.0184516","article-title":"A collaborative approach for research paper recommender system","volume":"12","author":"Haruna","year":"2017","journal-title":"PLoS ONE"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1504\/IJBSR.2021.111753","article-title":"Recommender Systems: An Over-view, Research Trends, and Future Directions","volume":"15","author":"Singh","year":"2021","journal-title":"International J. Bus. Syst. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"51246","DOI":"10.1109\/ACCESS.2020.2980589","article-title":"A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context","volume":"8","author":"Sakib","year":"2020","journal-title":"IEEE Access"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Pawlicka, A., Pawlicki, M., Kozik, R., and Chora\u015b, R. (2021). A Systematic Review of Recommender Systems and Their Applications in Cybersecurity. Sensors, 21.","DOI":"10.3390\/s21155248"},{"key":"ref_15","first-page":"1","article-title":"Early predictive model for breast cancer classification using blended ensemble learning","volume":"13","author":"Mahesh","year":"2022","journal-title":"Int. J. Syst. Assur. Eng. Manag."},{"key":"ref_16","first-page":"7427409","article-title":"Hybrid Algorithm Based on Content and Collaborative Filtering in Recommendation System Optimization and Simulation","volume":"2021","author":"Li","year":"2021","journal-title":"Sci. Program."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"126957","DOI":"10.1109\/ACCESS.2022.3221451","article-title":"Cervical Cancer Diagnosis Using Intelligent Living Behavior of Artificial Jellyfish Optimized With Artificial Neural Network","volume":"10","author":"Devarajan","year":"2022","journal-title":"IEEE Access"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2022\/4649510","article-title":"Performance Analysis of XGBoost Ensemble Methods for Survivability with the Classification of Breast Cancer","volume":"2022","author":"Mahesh","year":"2022","journal-title":"J. Sensors"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"113764","DOI":"10.1016\/j.eswa.2020.113764","article-title":"A survey of research hotspots and frontier trends of recommendation systems from the perspective of knowledge graph","volume":"165","author":"Shao","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"012011","DOI":"10.1088\/1757-899X\/1085\/1\/012011","article-title":"Machine Learning Techniques for Recommender Systems\u2014A Comparative Case Analysis","volume":"1085","author":"Thomas","year":"2021","journal-title":"IOP Conf. Series: Mater. Sci. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Beltagy, I., Lo, K., and Cohan, A. (2019). SciBERT: A Pretrained Language Model for Scientific Text. arXiv.","DOI":"10.18653\/v1\/D19-1371"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Osman, N.A., Noah, S.A.M., Darwich, M., and Mohd, M. (2021). Integrating contextual sentiment analysis in collaborative recommender systems. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0248695"},{"key":"ref_23","unstructured":"Sanh, V., Debut, L., Chaumond, J., and Wolf, T. (2019). DistilBERT, a distilled version of BERT: Smaller, faster, cheaper and lighter. arXiv."},{"key":"ref_24","unstructured":"Indraneel, A., Sai Pranav, K., and Mamatha, H.R. (2023, January 30). Hybrid Recommendation System for Scientific Literature. Lecture Notes on Data Engineering and Communications Technologies. Available online: https:\/\/www.springerprofessional.de\/en\/hybrid-recommendation-system-for-scientific-literature\/18874338."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ghosh, P., and Mahesh, T.R. (2016, January 18\u201319). A privacy preserving mutual authentication protocol for RFID based automated toll collection system. Proceedings of the 2016 International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India.","DOI":"10.1109\/ICTBIG.2016.7892668"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Haruna, K., Ismail, M.A., Bichi, A.B., Chang, V., Wibawa, S., and Herawan, T. (2018, January 2\u20135). A Citation-Based Recommender System for Scholarly Paper Recommendation. Proceedings of the International Conference on Computational Science and Its Applications\u2014ICSA 2018, Melbourne, VIC, Australia.","DOI":"10.1007\/978-3-319-95162-1_35"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.ins.2018.08.046","article-title":"A novel recommendation approach based on chronological cohesive units in content consuming logs","volume":"470","author":"Kim","year":"2019","journal-title":"Inf. Sci."},{"key":"ref_28","unstructured":"Wu, S., Tang, Y., Zhu, Y., Wang, L., Xie, X., and Tan, T. (February, January 27). Session-Based Recommendation with Graph Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence, Honolulu, HI, USA."}],"container-title":["Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-8954\/11\/2\/81\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:24:24Z","timestamp":1760120664000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-8954\/11\/2\/81"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,4]]},"references-count":28,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["systems11020081"],"URL":"https:\/\/doi.org\/10.3390\/systems11020081","relation":{},"ISSN":["2079-8954"],"issn-type":[{"value":"2079-8954","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,4]]}}}