{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T16:49:49Z","timestamp":1783615789199,"version":"3.55.0"},"reference-count":125,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,9,15]],"date-time":"2023-09-15T00:00:00Z","timestamp":1694736000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MTI"],"abstract":"<jats:p>The fast growth of data in the academic field has contributed to making recommendation systems for scientific papers more popular. Content-based filtering (CBF), a pivotal technique in recommender systems (RS), holds particular significance in the realm of scientific publication recommendations. In a content-based scientific publication RS, recommendations are composed by observing the features of users and papers. Content-based recommendation encompasses three primary steps, namely, item representation, user modeling, and recommendation generation. A crucial part of generating recommendations is the user modeling process. Nevertheless, this step is often neglected in existing content-based scientific publication RS. Moreover, most existing approaches do not capture the semantics of user models and papers. To address these limitations, in this paper we present a transparent Recommendation and Interest Modeling Application (RIMA), a content-based scientific publication RS that implicitly derives user interest models from their authored papers. To address the semantic issues, RIMA combines word embedding-based keyphrase extraction techniques with knowledge bases to generate semantically-enriched user interest models, and additionally leverages pretrained transformer sentence encoders to represent user models and papers and compute their similarities. The effectiveness of our approach was assessed through an offline evaluation by conducting extensive experiments on various datasets along with user study (N = 22), demonstrating that (a) combining SIFRank and SqueezeBERT as an embedding-based keyphrase extraction method with DBpedia as a knowledge base improved the quality of the user interest modeling step, and (b) using the msmarco-distilbert-base-tas-b sentence transformer model achieved better results in the recommendation generation step.<\/jats:p>","DOI":"10.3390\/mti7090091","type":"journal-article","created":{"date-parts":[[2023,9,15]],"date-time":"2023-09-15T04:06:13Z","timestamp":1694750773000},"page":"91","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Semantic Interest Modeling and Content-Based Scientific Publication Recommendation Using Word Embeddings and Sentence Encoders"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4105-8896","authenticated-orcid":false,"given":"Mouadh","family":"Guesmi","sequence":"first","affiliation":[{"name":"Social Computing Group, Faculty of Engineering, University of Duisburg-Essen, 47057 Duisburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1311-7852","authenticated-orcid":false,"given":"Mohamed Amine","family":"Chatti","sequence":"additional","affiliation":[{"name":"Social Computing Group, Faculty of Engineering, University of Duisburg-Essen, 47057 Duisburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lamees","family":"Kadhim","sequence":"additional","affiliation":[{"name":"Social Computing Group, Faculty of Engineering, University of Duisburg-Essen, 47057 Duisburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shoeb","family":"Joarder","sequence":"additional","affiliation":[{"name":"Social Computing Group, Faculty of Engineering, University of Duisburg-Essen, 47057 Duisburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2691-0267","authenticated-orcid":false,"given":"Qurat Ul","family":"Ain","sequence":"additional","affiliation":[{"name":"Social Computing Group, Faculty of Engineering, University of Duisburg-Essen, 47057 Duisburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.eij.2015.06.005","article-title":"Recommendation systems: Principles, methods and evaluation","volume":"16","author":"Isinkaye","year":"2015","journal-title":"Egypt. Inform. J."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Kaya, M., Birinci, \u015e., Kawash, J., and Alhajj, R. (2020). Putting Social Media and Networking Data in Practice for Education, Planning, Prediction and Recommendation, Springer International Publishing.","DOI":"10.1007\/978-3-030-33698-1"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/s00799-015-0156-0","article-title":"Paper recommender systems: A literature survey","volume":"17","author":"Beel","year":"2016","journal-title":"Int. J. Digit. Libr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"9324","DOI":"10.1109\/ACCESS.2018.2890388","article-title":"Scientific paper recommendation: A survey","volume":"7","author":"Bai","year":"2019","journal-title":"IEEE Access"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1109\/JAS.2021.1003919","article-title":"An overview of recommendation techniques and their applications in healthcare","volume":"8","author":"Yue","year":"2021","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1007\/s00799-022-00339-w","article-title":"Scientific paper recommendation systems: A literature review of recent publications","volume":"23","author":"Kreutz","year":"2022","journal-title":"Int. J. Digit. Libr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1007\/978-3-319-97289-3_20","article-title":"Research paper recommender systems on big scholarly data","volume":"Volume 15","author":"Chen","year":"2018","journal-title":"Proceedings of the Knowledge Management and Acquisition for Intelligent Systems: 15th Pacific Rim Knowledge Acquisition Workshop, PKAW 2018"},{"key":"ref_8","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_9","doi-asserted-by":"crossref","unstructured":"Hassan, H.A.M. (2017, January 13\u201316). Personalized research paper recommendation using deep learning. Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, Taichung City, Taiwan.","DOI":"10.1145\/3079628.3079708"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Nair, A.M., Benny, O., and George, J. (2021, January 5\u201310). Content based scientific article recommendation system using deep learning technique. Proceedings of the Inventive Systems and Control: ICISC, Divnomorskoe, Russia.","DOI":"10.1007\/978-981-16-1395-1_70"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Singh, R., Gaonkar, G., Bandre, V., Sarang, N., and Deshpande, S. (2023, January 28\u201330). Scientific Paper Recommendation System. Proceedings of the 2023 IEEE 8th International Conference for Convergence in Technology (I2CT), Shanghai, China.","DOI":"10.1109\/I2CT57861.2023.10126196"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Tanner, W., Akbas, E., and Hasan, M. (2019, January 25\u201327). Paper recommendation based on citation relation. Proceedings of the 2019 IEEE International Conference on Big Data, Belgrade, Serbia.","DOI":"10.1109\/BigData47090.2019.9006200"},{"key":"ref_13","first-page":"817","article-title":"Keywords-driven and popularity-aware paper recommendation based on undirected paper citation graph","volume":"2020","author":"Liu","year":"2020","journal-title":"Complexity"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Sinha, A., Shen, Z., Song, Y., Ma, H., Eide, D., Hsu, B.J., and Wang, K. (2015, January 26\u201331). An overview of microsoft academic service (mas) and applications. Proceedings of the 24th International Conference on World Wide Web, Vancouver, BC, Canada.","DOI":"10.1145\/2740908.2742839"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Beel, J., Aizawa, A., Breitinger, C., and Gipp, B. (2017, January 19\u201323). Mr. DLib: Recommendations-as-a-service (RaaS) for academia. Proceedings of the 2017 ACM\/IEEE Joint Conference on Digital Libraries (JCDL), Toronto, ON, Canada.","DOI":"10.1109\/JCDL.2017.7991606"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1007\/s13278-023-01056-1","article-title":"A hybrid recommendation system for researchgate academic social network","volume":"13","author":"Mataoui","year":"2023","journal-title":"Soc. Netw. Anal. Min."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3837","DOI":"10.1007\/s11192-022-04420-8","article-title":"A novel hybrid paper recommendation system using deep learning","volume":"127","author":"Kaya","year":"2022","journal-title":"Scientometrics"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.ins.2022.09.064","article-title":"SHARE: Designing multiple criteria-based personalized research paper recommendation system","volume":"617","author":"Chaudhuri","year":"2022","journal-title":"Inf. Sci."},{"key":"ref_19","unstructured":"Mohamed, H.A.I.M. (2020). Deep Learning Models for Research Paper Recommender Systems. [Ph.D. Thesis, Roma Tre University]."},{"key":"ref_20","first-page":"33","article-title":"A Review on Personalized Academic Paper Recommendation","volume":"12","author":"Zhi","year":"2019","journal-title":"Comput. Inf. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Ricci, F., Rokach, L., and Shapira, B. (2010). Recommender Systems Handbook, Springer.","DOI":"10.1007\/978-0-387-85820-3"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1561\/1500000078","article-title":"Extracting, Mining and Predicting Users\u2019 Interests from Social Media","volume":"14","author":"Zarrinkalam","year":"2020","journal-title":"Found. Trends Inf. Retr."},{"key":"ref_23","unstructured":"Chaudhuri, A., Samanta, D., and Sarma, M. (2021). Modeling user behaviour in research paper recommendation system. arXiv."},{"key":"ref_24","unstructured":"Hassan, H.A.M., Sansonetti, G., Gasparetti, F., Micarelli, A., and Beel, J. (2019, January 19\u201321). Bert, elmo, use and infersent sentence encoders: The panacea for research-paper recommendation?. Proceedings of the RecSys (Late-Breaking Results), Kuching, Malaysia."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Guo, G., Chen, B., Zhang, X., Liu, Z., Dong, Z., and He, X. (2020, January 8\u201311). Leveraging title-abstract attentive semantics for paper recommendation. Proceedings of the AAAI Conference on Artificial Intelligence, Hong Kong, China.","DOI":"10.1609\/aaai.v34i01.5335"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"10896","DOI":"10.1109\/ACCESS.2020.2965087","article-title":"SIFRank: A New Baseline for Unsupervised Keyphrase Extraction Based on Pre-Trained Language Model","volume":"8","author":"Sun","year":"2020","journal-title":"IEEE Access"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Iandola, F.N., Shaw, A.E., Krishna, R., and Keutzer, K.W. (2020). SqueezeBERT: What can computer vision teach NLP about efficient neural networks?. arXiv.","DOI":"10.18653\/v1\/2020.sustainlp-1.17"},{"key":"ref_28","first-page":"140134","article-title":"DBpedia\u2014A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia","volume":"6","author":"Lehmann","year":"2014","journal-title":"Semant. Web J."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Chatti, M.A., Ji, F., Guesmi, M., Muslim, A., Singh, R.K., and Joarder, S.A. (2021, January 22\u201324). Simt: A semantic interest modeling toolkit. Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, Adjunct Proceedings, Singapore.","DOI":"10.1145\/3450614.3461676"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1007\/s11257-018-9207-8","article-title":"Inferring user interests in microblogging social networks: A survey","volume":"28","author":"Piao","year":"2018","journal-title":"User Model. User-Adapt. Interact."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"106227","DOI":"10.1016\/j.knosys.2020.106227","article-title":"Mining user interest based on personality-aware hybrid filtering in social networks","volume":"206","author":"Dhelim","year":"2020","journal-title":"Knowl.-Based Syst."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Liu, K., Chen, W., Bu, J., Chen, C., and Zhang, L. (2007, January 10\u201315). User modeling for recommendation in blogspace. Proceedings of the 2007 IEEE\/WIC\/ACM International Conferences on Web Intelligence and Intelligent Agent Technology-Workshops, Fukuoka, Japan.","DOI":"10.1109\/WI-IATW.2007.23"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Pratama, B.Y., and Sarno, R. (2015, January 25\u201326). Personality classification based on Twitter text using Naive Bayes, KNN and SVM. Proceedings of the 2015 International Conference on Data and Software Engineering (ICoDSE), Yogyakarta, Indonesia.","DOI":"10.1109\/ICODSE.2015.7436992"},{"key":"ref_34","unstructured":"Stern, M., Beck, J., and Woolf, B.P. (1999). Naive Bayes Classifiers for User Modeling, Center for Knowledge Communication, Computer Science Department, University of Massachusetts."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Michelson, M., and Macskassy, S.A. (2010, January 14\u201318). Discovering users\u2019 topics of interest on twitter: A first look. Proceedings of the Fourth Workshop on Analytics for Noisy Unstructured Text Data, Brisbane, Australia.","DOI":"10.1145\/1871840.1871852"},{"key":"ref_36","first-page":"426","article-title":"Wiki-lda: A mixed-method approach for effective interest mining on twitter data","volume":"Volume 1","author":"Pu","year":"2016","journal-title":"Proceedings of the 8th International Conference on Computer Supported Education (CSEDU)"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Caragea, C., Bulgarov, F., Godea, A., and Gollapalli, S.D. (2014, January 27\u201329). Citation-enhanced keyphrase extraction from research papers: A supervised approach. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Kuala Lumpur, Malaysia.","DOI":"10.3115\/v1\/D14-1150"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Bennani-Smires, K., Musat, C., Hossmann, A., Baeriswyl, M., and Jaggi, M. (2018). Simple unsupervised keyphrase extraction using sentence embeddings. arXiv.","DOI":"10.18653\/v1\/K18-1022"},{"key":"ref_39","unstructured":"Liu, Z., Huang, W., Zheng, Y., and Sun, M. (November, January 30). Automatic Keyphrase Extraction via Topic Decomposition. Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, Wuhan, China."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1108\/eb026526","article-title":"A statistical interpretation of term specificity and its application in retrieval","volume":"28","author":"Jones","year":"1972","journal-title":"J. Doc."},{"key":"ref_41","unstructured":"Rose, S., Engel, D., Cramer, N., and Cowley, W. (2010). Text Mining: Applications and Theory, John Wiley & Sons, Ltd."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1007\/978-3-319-76941-7_80","article-title":"Yake! collection-independent automatic keyword extractor","volume":"Volume 40","author":"Campos","year":"2018","journal-title":"Proceedings of the Advances in Information Retrieval: 40th European Conference on IR Research, ECIR 2018"},{"key":"ref_43","unstructured":"Mihalcea, R., and Tarau, P. (2004, January 21\u201323). TextRank: Bringing Order into Text. Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, Barcelona, Spain."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Wan, X., and Xiao, J. (2008, January 18\u201322). CollabRank: Towards a Collaborative Approach to Single-Document Keyphrase Extraction. Proceedings of the COLING, Manchester, UK.","DOI":"10.3115\/1599081.1599203"},{"key":"ref_45","first-page":"855","article-title":"Single Document Keyphrase Extraction Using Neighborhood Knowledge","volume":"Volume 2","author":"Wan","year":"2008","journal-title":"Proceedings of the 23rd National Conference on Artificial Intelligence, AAAI\u201908"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Florescu, C., and Caragea, C. (2017, January 1\u20134). PositionRank: An Unsupervised Approach to Keyphrase Extraction from Scholarly Documents. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vancouver, BC, Canada.","DOI":"10.18653\/v1\/P17-1102"},{"key":"ref_47","unstructured":"Bougouin, A., Boudin, F., and Daille, B. (2013, January 28\u201330). Topicrank: Graph-based topic ranking for keyphrase extraction. Proceedings of the International Joint Conference on Natural Language Processing (IJCNLP), Cluj-Napoca, Romania."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Boudin, F. (2018). Unsupervised keyphrase extraction with multipartite graphs. arXiv.","DOI":"10.18653\/v1\/N18-2105"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-3-319-66562-7_1","article-title":"Exploring the use of linked open data for user research interest modeling","volume":"Volume 12","author":"Manrique","year":"2017","journal-title":"Proceedings of the Advances in Computing: 12th Colombian Conference, CCC 2017"},{"key":"ref_50","unstructured":"Liang, Y., and Zaki, M.J. (2021). Keyphrase Extraction Using Neighborhood Knowledge Based on Word Embeddings. arXiv."},{"key":"ref_51","unstructured":"Le, Q., and Mikolov, T. (2014, January 5). Distributed representations of sentences and documents. Proceedings of the International Conference on Machine Learning, PMLR, Xi\u2019an, China."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Pagliardini, M., Gupta, P., and Jaggi, M. (2018, January 1\u20136). Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, New York, NY, USA.","DOI":"10.18653\/v1\/N18-1049"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Peters, M.E., Neumann, M., Iyyer, M., Gardner, M., Clark, C., Lee, K., and Zettlemoyer, L. (2018, January 4\u20138). Deep Contextualized Word Representations. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, New Orleans, LA, USA.","DOI":"10.18653\/v1\/N18-1202"},{"key":"ref_54","unstructured":"Arora, S., Liang, Y., and Ma, T. (2017, January 24\u201326). A Simple but Tough-to-Beat Baseline for Sentence Embeddings. Proceedings of the International Conference on Learning Representations, Toulon, France."},{"key":"ref_55","first-page":"36","article-title":"Wiki-MID: A very large multi-domain interests dataset of Twitter users with mappings to Wikipedia","volume":"Volume 17","author":"Faralli","year":"2018","journal-title":"Proceedings of the The Semantic Web\u2013ISWC 2018: 17th International Semantic Web Conference"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Narducci, F., Musto, C., Semeraro, G., Lops, P., and De Gemmis, M. (2013, January 24\u201327). Leveraging encyclopedic knowledge for transparent and serendipitous user profiles. Proceedings of the International Conference on User Modeling, Adaptation, and Personalization, Atlantic City, NJ, USA.","DOI":"10.1007\/978-3-642-38844-6_36"},{"key":"ref_57","unstructured":"Jadhav, A.S., Purohit, H., Kapanipathi, P., Anantharam, P., Ranabahu, A.H., Nguyen, V., Mendes, P.N., Smith, A.G., Cooney, M., and Sheth, A.P. (2023, April 03). Twitris 2.0: Semantically Empowered System for Understanding Perceptions from Social Data. Available online: https:\/\/corescholar.libraries.wright.edu\/cgi\/viewcontent.cgi?article=1253&context=knoesis."},{"key":"ref_58","first-page":"187","article-title":"A knowledge-base oriented approach for automatic keyword extraction","volume":"17","author":"Gagnon","year":"2013","journal-title":"Comput. Sist."},{"key":"ref_59","unstructured":"Lu, C., Lam, W., and Zhang, Y. (2012, January 4\u20136). Twitter user modeling and tweets recommendation based on wikipedia concept graph. Proceedings of the Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence, Shanghai, China."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/meet.2011.14504801186","article-title":"Wikipedia-based topic clustering for microblogs","volume":"48","author":"Xu","year":"2011","journal-title":"Proc. Am. Soc. Inf. Sci. Technol."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1145\/3015297.3015298","article-title":"On the quality of semantic interest profiles for onine social network consumers","volume":"16","author":"Besel","year":"2016","journal-title":"ACM SIGAPP Appl. Comput. Rev."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Piao, G., and Breslin, J.G. (2016, January 24\u201328). User modeling on Twitter with WordNet Synsets and DBpedia concepts for personalized recommendations. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, Indianapolis, IN, USA.","DOI":"10.1145\/2983323.2983908"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Piao, G., and Breslin, J.G. (2016, January 25\u201328). Analyzing aggregated semantics-enabled user modeling on Google+ and Twitter for personalized link recommendations. Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization, Phoenix, AZ, USA.","DOI":"10.1145\/2930238.2930278"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Piao, G., and Breslin, J.G. (2016, January 20\u201322). Exploring dynamics and semantics of user interests for user modeling on Twitter for link recommendations. Proceedings of the 12th International Conference on Semantic Systems, Singapore.","DOI":"10.1145\/2993318.2993332"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1007\/s11257-006-9023-4","article-title":"A content-collaborative recommender that exploits WordNet-based user profiles for neighborhood formation","volume":"17","author":"Degemmis","year":"2007","journal-title":"User Model. User-Adapt. Interact."},{"key":"ref_66","unstructured":"Lops, P., de Gemmis, M., Semeraro, G., Musto, C., Narducci, F., and Bux, M. (2009). Web Personalization in Intelligent Environments, Springer."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s11257-012-9131-2","article-title":"Cross-system user modeling and personalization on the social web","volume":"23","author":"Abel","year":"2013","journal-title":"User Model. User-Adapt. Interact."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Yu, X., Ma, H., Hsu, B.J., and Han, J. (2014, January 11\u201314). On building entity recommender systems using user click log and freebase knowledge. Proceedings of the 7th ACM International Conference on Web Search and Data Mining, Warsaw, Poland.","DOI":"10.1145\/2556195.2556233"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Manrique, R., and Mari\u00f1o, O. (2017, January 21\u201323). How does the size of a document affect linked open data user modeling strategies?. Proceedings of the International Conference on Web Intelligence, Poznan, Poland.","DOI":"10.1145\/3106426.3109440"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1007\/978-3-642-31753-8_31","article-title":"Leveraging user modeling on the social web with linked data","volume":"Volume 12","author":"Abel","year":"2012","journal-title":"Proceedings of the Web Engineering: 12th International Conference, ICWE 2012"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Shen, W., Wang, J., Luo, P., and Wang, M. (2013, January 8\u201310). Linking named entities in tweets with knowledge base via user interest modeling. Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Fuzhou, China.","DOI":"10.1145\/2487575.2487686"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Renuka, S., Raj Kiran, G., and Rohit, P. (2020, January 22\u201324). An unsupervised content-based article recommendation system using natural language processing. Proceedings of the Data Intelligence and Cognitive Informatics ICDICI, Kyoto, Japan.","DOI":"10.1007\/978-981-15-8530-2_13"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Subathra, P., and Kumar, P. (2019, January 3\u20135). Recommending research article based on user queries using latent dirichlet allocation. Proceedings of the 2nd ICSCSP Soft Computing and Signal Processing, Alcala de Henares, Spain.","DOI":"10.1007\/978-981-15-2475-2_15"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1007\/978-981-15-8101-4_51","article-title":"Paper recommend based on LDA and PageRank","volume":"Volume 6","author":"Tao","year":"2020","journal-title":"Proceedings of the Artificial Intelligence and Security: 6th International Conference, ICAIS 2020"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Collins, A., and Beel, J. (2019, January 11\u201315). Document embeddings vs. keyphrases vs. terms for recommender systems: A large-scale online evaluation. Proceedings of the 2019 ACM\/IEEE Joint Conference on Digital Libraries (JCDL), Chapel Hill, NC, USA.","DOI":"10.1109\/JCDL.2019.00027"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"188628","DOI":"10.1109\/ACCESS.2020.3031281","article-title":"A hybrid model based on LFM and BiGRU toward research paper recommendation","volume":"8","author":"Zhao","year":"2020","journal-title":"IEEE Access"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"106438","DOI":"10.1016\/j.knosys.2020.106438","article-title":"Paper recommendation based on heterogeneous network embedding","volume":"210","author":"Ali","year":"2020","journal-title":"Knowl.-Based Syst."},{"key":"ref_78","unstructured":"Bereczki, M. (2021). Graph neural networks for article recommendation based on implicit user feedback and content. arXiv."},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Rios, F., Rizzo, P., Puddu, F., Romeo, F., Lentini, A., Asaro, G., Rescalli, F., Bolchini, C., and Cremonesi, P. (2022, January 13\u201316). Recommending Relevant Papers to Conference Participants: A Deep Learning Driven Content-based Approach. Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, Adjunct Proceedings, Omaha, NE, USA.","DOI":"10.1145\/3511047.3536413"},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Ferrara, F., Pudota, N., and Tasso, C. (2011, January 20\u201321). A keyphrase-based paper recommender system. Proceedings of the Digital Libraries and Archives: 7th Italian Research Conference, IRCDL 2011, Pisa, Italy.","DOI":"10.1007\/978-3-642-27302-5_2"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1007\/s00799-021-00301-2","article-title":"Hidden features identification for designing an efficient research article recommendation system","volume":"22","author":"Chaudhuri","year":"2021","journal-title":"Int. J. Digit. Libr."},{"key":"ref_82","unstructured":"Hong, K., Jeon, H., and Jeon, C. (2012, January 21\u201323). UserProfile-based personalized research paper recommendation system. Proceedings of the 2012 8th International Conference on Computing and Networking Technology (INC, ICCIS and ICMIC), Shanghai, China."},{"key":"ref_83","first-page":"106","article-title":"Personalized research paper recommendation system using keyword extraction based on UserProfile","volume":"8","author":"Hong","year":"2013","journal-title":"J. Converg. Inf. Technol."},{"key":"ref_84","unstructured":"Gautam, J., and Kumar, E. (2012, January 19\u201320). An improved framework for tag-based academic information sharing and recommendation system. Proceedings of the World Congress on Engineering, Wuhan, China."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Beel, J., Langer, S., Genzmehr, M., and N\u00fcrnberger, A. (2013, January 20\u201324). Introducing Docear\u2019s research paper recommender system. Proceedings of the 13th ACM\/IEEE-CS Joint Conference on Digital Libraries, Cologne, Germany.","DOI":"10.1145\/2467696.2467786"},{"key":"ref_86","first-page":"1045","article-title":"The Architecture and Datasets of Docear\u2019s Research Paper Recommender System","volume":"20","author":"Beel","year":"2014","journal-title":"D-Lib Mag."},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Jomsri, P., Sanguansintukul, S., and Choochaiwattana, W. (2010, January 20\u201323). A framework for tag-based research paper recommender system: An IR approach. Proceedings of the 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops, Perth, WA, Australia.","DOI":"10.1109\/WAINA.2010.35"},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Al Alshaikh, M., Uchyigit, G., and Evans, R. (2017, January 24\u201327). A research paper recommender system using a Dynamic Normalized Tree of Concepts model for user modelling. Proceedings of the 2017 11th International Conference on Research Challenges in Information Science (RCIS), Auckland, New Zealand.","DOI":"10.1109\/RCIS.2017.7956538"},{"key":"ref_89","unstructured":"Lee, J., Lee, K., and Kim, J.G. (2013). Personalized academic research paper recommendation system. arXiv."},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Sugiyama, K., and Kan, M.Y. (2010, January 23\u201326). Scholarly paper recommendation via user\u2019s recent research interests. Proceedings of the 10th Annual Joint Conference on Digital Libraries, Houston, TX, USA.","DOI":"10.1145\/1816123.1816129"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"e273","DOI":"10.7717\/peerj-cs.273","article-title":"Influence of tweets and diversification on serendipitous research paper recommender systems","volume":"6","author":"Nishioka","year":"2020","journal-title":"PeerJ Comput. Sci."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1007\/978-3-030-34058-2_7","article-title":"Research paper recommender system with serendipity using tweets vs. diversification","volume":"Volume 21","author":"Nishioka","year":"2019","journal-title":"Proceedings of the Digital Libraries at the Crossroads of Digital Information for the Future: 21st International Conference on Asia-Pacific Digital Libraries, ICADL 2019"},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1007\/978-3-030-30760-8_29","article-title":"Towards serendipitous research paper recommender using tweets and diversification","volume":"Volume 23","author":"Nishioka","year":"2019","journal-title":"Proceedings of the Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019"},{"key":"ref_94","doi-asserted-by":"crossref","unstructured":"Bulut, B., Kaya, B., Alhajj, R., and Kaya, M. (2018, January 18\u201321). A paper recommendation system based on user\u2019s research interests. Proceedings of the 2018 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), San Francisco, CA, USA.","DOI":"10.1109\/ASONAM.2018.8508313"},{"key":"ref_95","doi-asserted-by":"crossref","unstructured":"Bulut, B., Kaya, B., and Kaya, M. (2019, January 6\u20137). A Paper Recommendation System Based on User Interest and Citations. Proceedings of the 2019 1st International Informatics and Software Engineering Conference (UBMYK), Ankara, Turkey.","DOI":"10.1109\/UBMYK48245.2019.8965533"},{"key":"ref_96","first-page":"171","article-title":"Academic paper recommendation based on clustering and pattern matching","volume":"Volume 2","author":"Chen","year":"2019","journal-title":"Proceedings of the Artificial Intelligence: Second CCF International Conference, ICAI 2019"},{"key":"ref_97","doi-asserted-by":"crossref","unstructured":"Amami, M., Pasi, G., Stella, F., and Faiz, R. (2016, January 11\u201314). An LDA-Based Approach to Scientific Paper Recommendation. Proceedings of the International Conference on Applications of Natural Language to Data Bases, Boston, MA, USA.","DOI":"10.1007\/978-3-319-41754-7_17"},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"Lin, S.J., Lee, G., and Peng, S.L. (2020, January 14\u201316). Academic article recommendation by considering the research field trajectory. Proceedings of the International Conference on Innovative Computing and Cutting-Edge Technologies, Uttarakhand, India.","DOI":"10.1007\/978-3-030-65407-8_39"},{"key":"ref_99","first-page":"051006","article-title":"Application of content-based approach in research paper recommendation system for a digital library","volume":"5","author":"Philip","year":"2014","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_100","doi-asserted-by":"crossref","unstructured":"Nascimento, C., Laender, A.H., da Silva, A.S., and Gon\u00e7alves, M.A. (2011, January 19). A source independent framework for research paper recommendation. Proceedings of the 11th Annual International ACM\/IEEE Joint Conference on Digital Libraries, Toronto, ON, Canada.","DOI":"10.1145\/1998076.1998132"},{"key":"ref_101","first-page":"255","article-title":"An effective academic research papers recommendation for non-profiled users","volume":"8","author":"Hanyurwimfura","year":"2015","journal-title":"Int. J. Hybrid Inf. Technol."},{"key":"ref_102","unstructured":"Guesmi, M., Chatti, M.A., Sun, Y., Zumor, S., Ji, F., Muslim, A., Vorgerd, L., and Joarder, S.A. (2021, January 15\u201318). Open, Scrutable and Explainable Interest Models for Transparent Recommendation. Proceedings of the IUI Workshops, Rome, Italy."},{"key":"ref_103","unstructured":"Guesmi, M., Chatti, M.A., Vorgerd, L., Joarder, S., Zumor, S., Sun, Y., Ji, F., and Muslim, A. Proceedings of the Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, Uxbridge, UK, 17\u201318 December 2021."},{"key":"ref_104","unstructured":"Guesmi, M., Chatti, M.A., Vorgerd, L., Joarder, S.A., Ain, Q.U., Ngo, T., Zumor, S., Sun, Y., Ji, F., and Muslim, A. (October, January 27). Input or Output: Effects of Explanation Focus on the Perception of Explainable Recommendation with Varying Level of Details. Proceedings of the IntRS@ RecSys, Amsterdam, The Netherlands."},{"key":"ref_105","unstructured":"Guesmi, M., Chatti, M.A., Ghorbani-Bavani, J., Joarder, S., Ain, Q.U., and Alatrash, R. (2022). What if Interactive Explanation in a Scientific Literature Recommender System. arXiv."},{"key":"ref_106","doi-asserted-by":"crossref","unstructured":"Chatti, M.A., Guesmi, M., Vorgerd, L., Ngo, T., Joarder, S., Ain, Q.U., and Muslim, A. (2022, January 27\u201329). Is More Always Better? The Effects of Personal Characteristics and Level of Detail on the Perception of Explanations in a Recommender System. Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, Nanjing, China.","DOI":"10.1145\/3503252.3531304"},{"key":"ref_107","unstructured":"Guesmi, M., Chatti, M.A., Vorgerd, L., Ngo, T., Joarder, S., Ain, Q.U., and Muslim, A. Proceedings of the Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, Turin, Italy, 4\u20138 July 2022."},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Guesmi, M., Chatti, M.A., Tayyar, A., Ain, Q.U., and Joarder, S. (2022). Interactive visualizations of transparent user models for self-actualization: A human-centered design approach. Multimodal Technol. Interact., 6.","DOI":"10.3390\/mti6060042"},{"key":"ref_109","doi-asserted-by":"crossref","unstructured":"Guesmi, M., Chatti, M.A., Joarder, S., Ain, Q.U., Siepmann, C., Ghanbarzadeh, H., and Alatrash, R. (2023). Justification vs. Transparency: Why and How Visual Explanations in a Scientific Literature Recommender System. Information, 14.","DOI":"10.3390\/info14070401"},{"key":"ref_110","doi-asserted-by":"crossref","unstructured":"Guesmi, M., Siepmann, C., Chatti, M.A., Joarder, S., Ain, Q.U., and Alatrash, R. (2023, January 3\u20136). Validation of the EDUSS Framework for Self-Actualization Based on Transparent User Models: A Qualitative Study. Proceedings of the Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, London, UK.","DOI":"10.1145\/3563359.3597379"},{"key":"ref_111","unstructured":"Bougouin, A., Boudin, F., and Daille, B. (2013, January 14\u201318). TopicRank: Graph-Based Topic Ranking for Keyphrase Extraction. Proceedings of the IJCNLP, Nagoya, Japan."},{"key":"ref_112","doi-asserted-by":"crossref","unstructured":"Jardine, J.G., and Teufel, S. (2014, January 26\u201330). Topical PageRank: A Model of Scientific Expertise for Bibliographic Search. Proceedings of the EACL, Gothenburg, Sweden.","DOI":"10.3115\/v1\/E14-1053"},{"key":"ref_113","doi-asserted-by":"crossref","unstructured":"Boudin, F. (2018, January 3\u201310). Unsupervised Keyphrase Extraction with Multipartite Graphs. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, New Orleans, LA, USA.","DOI":"10.18653\/v1\/N18-2105"},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.ins.2019.09.013","article-title":"YAKE! Keyword extraction from single documents using multiple local features","volume":"509","author":"Campos","year":"2020","journal-title":"Inf. Sci."},{"key":"ref_115","doi-asserted-by":"crossref","unstructured":"Hulth, A. (2003, January 11\u201312). Improved automatic keyword extraction given more linguistic knowledge. Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Sapporo, Japan.","DOI":"10.3115\/1119355.1119383"},{"key":"ref_116","doi-asserted-by":"crossref","unstructured":"Yu, P., and Wang, X. (2020, January 16). BERT-Based Named Entity Recognition in Chinese Twenty-Four Histories. Proceedings of the International Conference on Web Information Systems and Applications, Cham, Switzerland.","DOI":"10.1007\/978-3-030-60029-7_27"},{"key":"ref_117","unstructured":"Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., and Stoyanov, V. (2019). Roberta: A robustly optimized bert pretraining approach. arXiv."},{"key":"ref_118","first-page":"866","article-title":"Xlnet: Generalized autoregressive pretraining for language understanding","volume":"32","author":"Yang","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_119","doi-asserted-by":"crossref","unstructured":"Mendes, P., Jakob, M., Garc\u00eda-Silva, A., and Bizer, C. (2011, January 2\u20139). DBpedia spotlight: Shedding light on the web of documents. Proceedings of the 7th International Conference on Semantic Systems, New York, NY, USA.","DOI":"10.1145\/2063518.2063519"},{"key":"ref_120","doi-asserted-by":"crossref","unstructured":"Cheng, Y., Qiu, G., Bu, J., Liu, K., Han, Y., Wang, C., and Chen, C. (2008, January 21\u201325). Model bloggers\u2019 interests based on forgetting mechanism. Proceedings of the 17th International Conference on World Wide Web, Beijing, China.","DOI":"10.1145\/1367497.1367690"},{"key":"ref_121","doi-asserted-by":"crossref","unstructured":"Conneau, A., Kiela, D., Schwenk, H., Barrault, L., and Bordes, A. (2017). Supervised learning of universal sentence representations from natural language inference data. arXiv.","DOI":"10.18653\/v1\/D17-1070"},{"key":"ref_122","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_123","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1162\/COLI_a_00237","article-title":"SimLex-999: Evaluating Semantic Models with (Genuine) Similarity Estimation","volume":"41","author":"Hill","year":"2015","journal-title":"Comput. Linguist."},{"key":"ref_124","unstructured":"Asaadi, S., Mohammad, S., and Kiritchenko, S. (2019, January 4\u20138). Big BiRD: A large, fine-grained, bigram relatedness dataset for examining semantic composition. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Minneapolis, MI, USA."},{"key":"ref_125","doi-asserted-by":"crossref","unstructured":"Cer, D., Diab, M., Agirre, E., Lopez-Gazpio, I., and Specia, L. (2017). Semeval-2017 task 1: Semantic textual similarity-multilingual and cross-lingual focused evaluation. arXiv.","DOI":"10.18653\/v1\/S17-2001"}],"container-title":["Multimodal Technologies and Interaction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2414-4088\/7\/9\/91\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:51:32Z","timestamp":1760129492000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2414-4088\/7\/9\/91"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,15]]},"references-count":125,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2023,9]]}},"alternative-id":["mti7090091"],"URL":"https:\/\/doi.org\/10.3390\/mti7090091","relation":{},"ISSN":["2414-4088"],"issn-type":[{"value":"2414-4088","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,15]]}}}