Literatura científica selecionada sobre o tema "Recommender System (RS)"
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Artigos de revistas sobre o assunto "Recommender System (RS)"
Walia, Prof Ranjanroop. "Online Recommender System". International Journal for Research in Applied Science and Engineering Technology 9, n.º VII (30 de julho de 2021): 2569–77. http://dx.doi.org/10.22214/ijraset.2021.36424.
Texto completo da fonteLahlou, Fatima Zahra, Houda Benbrahim e Ismail Kassou. "Review Aware Recommender System". International Journal of Distributed Artificial Intelligence 10, n.º 2 (julho de 2018): 28–50. http://dx.doi.org/10.4018/ijdai.2018070102.
Texto completo da fonteKumar Sahni, Dheeraj. "Recommender System (RS): Challenges, Issues & Extensions". Mapana Journal of Sciences 21, n.º 1 (1 de janeiro de 2022): 73–92. http://dx.doi.org/10.12723/mjs.60.6.
Texto completo da fonteKang, Li Ting, e Yong Wang. "Seven Factors in Evaluating Recommender System". Applied Mechanics and Materials 472 (janeiro de 2014): 443–49. http://dx.doi.org/10.4028/www.scientific.net/amm.472.443.
Texto completo da fonteBajenaru, Victor, Steven Lavoie, Brett Benyo, Christopher Riker, Mitchell Colby e James Vaccaro. "Recommender System Metaheuristic for Optimizing Decision-Making Computation". Electronics 12, n.º 12 (14 de junho de 2023): 2661. http://dx.doi.org/10.3390/electronics12122661.
Texto completo da fonteVaidhehi, V., e R. Suchithra. "A Systematic Review of Recommender Systems in Education". International Journal of Engineering & Technology 7, n.º 3.4 (25 de junho de 2018): 188. http://dx.doi.org/10.14419/ijet.v7i3.4.16771.
Texto completo da fonteUsman, Abdulgafar, Abubakar Roko, Aminu B. Muhammad e Abba Almu. "Enhancing Personalized Book Recommender System". International Journal of Advanced Networking and Applications 14, n.º 03 (2022): 5486–92. http://dx.doi.org/10.35444/ijana.2022.14311.
Texto completo da fonteBatra, Priya, Anukriti Singh e T. S. Mahesh. "Efficient Characterization of Quantum Evolutions via a Recommender System". Quantum 5 (6 de dezembro de 2021): 598. http://dx.doi.org/10.22331/q-2021-12-06-598.
Texto completo da fonteYadav, Dharminder, Himani Maheshwari e Umesh Chandra. "An Approach Towards Hotel Recommender System". Journal of Computational and Theoretical Nanoscience 17, n.º 6 (1 de junho de 2020): 2605–12. http://dx.doi.org/10.1166/jctn.2020.8936.
Texto completo da fonteNugroho, Arseto Satriyo, Igi Ardiyanto e Teguh Bharata Adji. "User Curiosity Factor in Determining Serendipity of Recommender System". IJITEE (International Journal of Information Technology and Electrical Engineering) 5, n.º 3 (30 de setembro de 2021): 75. http://dx.doi.org/10.22146/ijitee.67553.
Texto completo da fonteTeses / dissertações sobre o assunto "Recommender System (RS)"
Sima, Xingyu. "La gestion des connaissances dans les petites et moyennes entreprises : un cadre adapté et complet". Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSEP047.
Texto completo da fonteKnowledge is vital for organizations, particularly in today’s Industry 4.0 context. Knowledge Management (KM) plays a critical role in an organization's success. Although KM has been relatively well-studied in large organizations, Small and Medium-sized Enterprises (SMEs) receive less attention. SMEs face unique challenges in KM, requiring a tailored KM framework. Our study aims to define a framework addressing their challenges while leveraging their inherent strengths. This thesis presents a dedicated and comprehensive SME KM framework, offering dedicated solutions from knowledge acquisition and representation to exploitation: (1) a dedicated knowledge acquisition process based on the Scrum framework, an agile methodology, (2) a dedicated knowledge representation model based on semi-structured KG, and (3) a dedicated knowledge exploitation process based on knowledge-relatedness RS. This research was conducted in collaboration with Axsens-bte, an SME specializing in consultancy and training. The partnership with Axsens-bte has provided invaluable insights and practical experiences, contributing to developing the proposed KM framework and highlighting its relevance and applicability in real-world SME contexts
Capítulos de livros sobre o assunto "Recommender System (RS)"
Zeng, Wanling, Yang Du, Dingqian Zhang, Zhili Ye e Zhumei Dou. "TUP-RS: Temporal User Profile Based Recommender System". In Artificial Intelligence and Soft Computing, 463–74. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91262-2_42.
Texto completo da fonteMagrani, Eduardo, e Paula Guedes Fernandes da Silva. "The Ethical and Legal Challenges of Recommender Systems Driven by Artificial Intelligence". In Multidisciplinary Perspectives on Artificial Intelligence and the Law, 141–68. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-41264-6_8.
Texto completo da fonteDhabliya, Dharmesh, Kshipra Jain, Manju Bargavi, Deepak, Anishkumar Dhablia, Jambi Ratna Raja Kumar, Ankur Gupta e Sabyasachi Pramanik. "Item Selection Using K-Means and Cosine Similarity". In AI-Driven Marketing Research and Data Analytics, 228–44. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2165-2.ch013.
Texto completo da fonteVaraprasad Rao M e Vishnu Murthy G. "DSS for Web Mining Using Recommendation System". In Advances in Data Mining and Database Management, 22–34. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1877-8.ch003.
Texto completo da fonteShelke, P. M., Suruchi Dedgaonkar e R. N. Bhimanpallewar. "Powering User Interface Design of Tourism Recommendation System with AI and ML". In Artificial Intelligence, Machine Learning and User Interface Design, 108–35. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815179606124010008.
Texto completo da fonteKumar, Sumit, Dr Vishal Shrivastava e Dr Vibhakar Pathak. "A BRIEF OVERVIEW ON SENTIMENT ANALYSIS BASED RECOMMENDATION SYSTEM". In Futuristic Trends in Computing Technologies and Data Sciences Volume 3 Book 4, 83–94. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bict4p2ch1.
Texto completo da fonteSielis, George A., Aimilia Tzanavari e George A. Papadopoulos. "Recommender Systems Review of Types, Techniques, and Applications". In Encyclopedia of Information Science and Technology, Third Edition, 7260–70. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-5888-2.ch714.
Texto completo da fonteSoliman, Khaled, Mahmood A. Mahmood, Ahmed El Azab e Hesham Ahmed Hefny. "A Survey of Recommender Systems and Geographical Recommendation Techniques". In GIS Applications in the Tourism and Hospitality Industry, 249–74. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5088-4.ch011.
Texto completo da fonteKarthick, G. S., e M. Sridhar. "Intelligent Healthcare Recommender Systems for Advanced Healthcare Informatics". In Advances in Healthcare Information Systems and Administration, 1–24. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-8913-0.ch001.
Texto completo da fonteRicci, Francesco, Quang Nhat Nguyen e Olga Averjanova. "Exploiting a Map-Based Interface in Conversational Recommender Systems for Mobile Travelers". In Tourism Informatics, 73–93. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-818-5.ch005.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Recommender System (RS)"
Lu, Kezhi, Qian Zhang, Guangquan Zhang e Jie Lu. "BERT-RS: A neural personalized recommender system with BERT". In Conference on Machine learning, Multi Agent and Cyber Physical Systems (FLINS 2022). WORLD SCIENTIFIC, 2023. http://dx.doi.org/10.1142/9789811269264_0046.
Texto completo da fonteZheng, Yong, Markus Zanker, Li Chen e Panagiotis Symeonidis. "Session details: Theme: System software and security: RS - recommender systems track". In SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3535442.
Texto completo da fonteLaskoski, Felipe F., e Alfredo Goldman. "CienTec Guide: Application and Online Evaluation of a Context-Based Recommender System in Cultural Heritage". In Simpósio Brasileiro de Sistemas de Informação. Sociedade Brasileira de Computação (SBC), 2022. http://dx.doi.org/10.5753/sbsi_estendido.2022.222608.
Texto completo da fonte"Session details: Theme: System software and security: RS - Recommender systems: Theory and applications track". In the 34th ACM/SIGAPP Symposium, editado por Markus Zanker, Li Chen, Panagiotis Symeonidis e Yong Zheng. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3297280.3329387.
Texto completo da fonte"Session details: Theme: System software and security: RS - Recommender systems: Theory and applications track". In SAC '19: The 34th ACM/SIGAPP Symposium on Applied Computing, editado por Markus Zanker, Li Chen, Panagiotis Symeonidis e Yong Zheng. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3329387.
Texto completo da fonteZheng, Yong, Li Chen, Markus Zanker e Panagiotis Symeonidis. "Session details: Theme: System software and security: RS - Recommender systems: Theory and applications track". In SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3462430.
Texto completo da fonteZanker, Markus, Panagiotis Symeonidis e Yong Zheng. "Session details: Theme: System software and security: RS - Recommender systems: Theory and applications track". In SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3389669.
Texto completo da fonte"Session details: System software and security: RS - recommender systems: theory, user interactions and applications track". In the 33rd Annual ACM Symposium, editado por Yong Zheng, Li Chen e Markus Zanker. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3167132.3258667.
Texto completo da fonte"Session details: System software and security: RS - recommender systems: theory, user interactions and applications track". In SAC 2018: Symposium on Applied Computing, editado por Yong Zheng, Li Chen e Markus Zanker. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3258667.
Texto completo da fonteSilva, Thiago, Adriano Pereira e Leonardo Rocha. "iRec: Um framework para modelos interativos em Sistemas de Recomendação". In Concurso de Teses e Dissertações. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/ctd.2023.229296.
Texto completo da fonte