Auswahl der wissenschaftlichen Literatur zum Thema „Recommender System (RS)“
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Zeitschriftenartikel zum Thema "Recommender System (RS)"
Walia, Prof Ranjanroop. „Online Recommender System“. International Journal for Research in Applied Science and Engineering Technology 9, Nr. VII (30.07.2021): 2569–77. http://dx.doi.org/10.22214/ijraset.2021.36424.
Der volle Inhalt der QuelleLahlou, Fatima Zahra, Houda Benbrahim und Ismail Kassou. „Review Aware Recommender System“. International Journal of Distributed Artificial Intelligence 10, Nr. 2 (Juli 2018): 28–50. http://dx.doi.org/10.4018/ijdai.2018070102.
Der volle Inhalt der QuelleKumar Sahni, Dheeraj. „Recommender System (RS): Challenges, Issues & Extensions“. Mapana Journal of Sciences 21, Nr. 1 (01.01.2022): 73–92. http://dx.doi.org/10.12723/mjs.60.6.
Der volle Inhalt der QuelleKang, Li Ting, und Yong Wang. „Seven Factors in Evaluating Recommender System“. Applied Mechanics and Materials 472 (Januar 2014): 443–49. http://dx.doi.org/10.4028/www.scientific.net/amm.472.443.
Der volle Inhalt der QuelleBajenaru, Victor, Steven Lavoie, Brett Benyo, Christopher Riker, Mitchell Colby und James Vaccaro. „Recommender System Metaheuristic for Optimizing Decision-Making Computation“. Electronics 12, Nr. 12 (14.06.2023): 2661. http://dx.doi.org/10.3390/electronics12122661.
Der volle Inhalt der QuelleVaidhehi, V., und R. Suchithra. „A Systematic Review of Recommender Systems in Education“. International Journal of Engineering & Technology 7, Nr. 3.4 (25.06.2018): 188. http://dx.doi.org/10.14419/ijet.v7i3.4.16771.
Der volle Inhalt der QuelleUsman, Abdulgafar, Abubakar Roko, Aminu B. Muhammad und Abba Almu. „Enhancing Personalized Book Recommender System“. International Journal of Advanced Networking and Applications 14, Nr. 03 (2022): 5486–92. http://dx.doi.org/10.35444/ijana.2022.14311.
Der volle Inhalt der QuelleBatra, Priya, Anukriti Singh und T. S. Mahesh. „Efficient Characterization of Quantum Evolutions via a Recommender System“. Quantum 5 (06.12.2021): 598. http://dx.doi.org/10.22331/q-2021-12-06-598.
Der volle Inhalt der QuelleYadav, Dharminder, Himani Maheshwari und Umesh Chandra. „An Approach Towards Hotel Recommender System“. Journal of Computational and Theoretical Nanoscience 17, Nr. 6 (01.06.2020): 2605–12. http://dx.doi.org/10.1166/jctn.2020.8936.
Der volle Inhalt der QuelleNugroho, Arseto Satriyo, Igi Ardiyanto und Teguh Bharata Adji. „User Curiosity Factor in Determining Serendipity of Recommender System“. IJITEE (International Journal of Information Technology and Electrical Engineering) 5, Nr. 3 (30.09.2021): 75. http://dx.doi.org/10.22146/ijitee.67553.
Der volle Inhalt der QuelleDissertationen zum Thema "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.
Der volle Inhalt der QuelleKnowledge 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
Buchteile zum Thema "Recommender System (RS)"
Zeng, Wanling, Yang Du, Dingqian Zhang, Zhili Ye und 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.
Der volle Inhalt der QuelleMagrani, Eduardo, und 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.
Der volle Inhalt der QuelleDhabliya, Dharmesh, Kshipra Jain, Manju Bargavi, Deepak, Anishkumar Dhablia, Jambi Ratna Raja Kumar, Ankur Gupta und 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.
Der volle Inhalt der QuelleVaraprasad Rao M und 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.
Der volle Inhalt der QuelleShelke, P. M., Suruchi Dedgaonkar und 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.
Der volle Inhalt der QuelleKumar, Sumit, Dr Vishal Shrivastava und 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.
Der volle Inhalt der QuelleSielis, George A., Aimilia Tzanavari und 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.
Der volle Inhalt der QuelleSoliman, Khaled, Mahmood A. Mahmood, Ahmed El Azab und 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.
Der volle Inhalt der QuelleKarthick, G. S., und 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.
Der volle Inhalt der QuelleRicci, Francesco, Quang Nhat Nguyen und 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.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Recommender System (RS)"
Lu, Kezhi, Qian Zhang, Guangquan Zhang und 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.
Der volle Inhalt der QuelleZheng, Yong, Markus Zanker, Li Chen und 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.
Der volle Inhalt der QuelleLaskoski, Felipe F., und 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.
Der volle Inhalt der Quelle„Session details: Theme: System software and security: RS - Recommender systems: Theory and applications track“. In the 34th ACM/SIGAPP Symposium, herausgegeben von Markus Zanker, Li Chen, Panagiotis Symeonidis und Yong Zheng. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3297280.3329387.
Der volle Inhalt der Quelle„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, herausgegeben von Markus Zanker, Li Chen, Panagiotis Symeonidis und Yong Zheng. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3329387.
Der volle Inhalt der QuelleZheng, Yong, Li Chen, Markus Zanker und 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.
Der volle Inhalt der QuelleZanker, Markus, Panagiotis Symeonidis und 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.
Der volle Inhalt der Quelle„Session details: System software and security: RS - recommender systems: theory, user interactions and applications track“. In the 33rd Annual ACM Symposium, herausgegeben von Yong Zheng, Li Chen und Markus Zanker. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3167132.3258667.
Der volle Inhalt der Quelle„Session details: System software and security: RS - recommender systems: theory, user interactions and applications track“. In SAC 2018: Symposium on Applied Computing, herausgegeben von Yong Zheng, Li Chen und Markus Zanker. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3258667.
Der volle Inhalt der QuelleSilva, Thiago, Adriano Pereira und 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.
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