Artículos de revistas sobre el tema "EFFICIENT RECOMMENDER SYSTEMS"
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Ribeiro, Marco Tulio, Nivio Ziviani, Edleno Silva De Moura, Itamar Hata, Anisio Lacerda y Adriano Veloso. "Multiobjective Pareto-Efficient Approaches for Recommender Systems". ACM Transactions on Intelligent Systems and Technology 5, n.º 4 (23 de enero de 2015): 1–20. http://dx.doi.org/10.1145/2629350.
Texto completoHuang, Zhen Hua, Dong Wang y Sheng Li Sun. "Efficient Mining of Skyrank Items in Recommender Systems". Advanced Materials Research 472-475 (febrero de 2012): 3450–54. http://dx.doi.org/10.4028/www.scientific.net/amr.472-475.3450.
Texto completoHawashin, Bilal, Shadi Alzubi, Tarek Kanan y Ayman Mansour. "An efficient semantic recommender method forArabic text". Electronic Library 37, n.º 2 (1 de abril de 2019): 263–80. http://dx.doi.org/10.1108/el-12-2018-0245.
Texto completoPasdar, Amirmohammad, Young Choon Lee, Tahereh Hassanzadeh y Khaled Almi’ani. "Resource Recommender for Cloud-Edge Engineering". Information 12, n.º 6 (25 de mayo de 2021): 224. http://dx.doi.org/10.3390/info12060224.
Texto completoJabbar, Muhammad, Qaisar Javaid, Muhammad Arif, Asim Munir y Ali Javed. "An Efficient and Intelligent Recommender System for Mobile Platform". October 2018 37, n.º 4 (1 de octubre de 2018): 463–80. http://dx.doi.org/10.22581/muet1982.1804.02.
Texto completoRadlinski, Filip, Craig Boutilier, Deepak Ramachandran y Ivan Vendrov. "Subjective Attributes in Conversational Recommendation Systems: Challenges and Opportunities". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 11 (28 de junio de 2022): 12287–93. http://dx.doi.org/10.1609/aaai.v36i11.21492.
Texto completoLuo, Chenhong, Yong Wang, Bo Li, Hanyang Liu, Pengyu Wang y Leo Yu Zhang. "An Efficient Approach to Manage Natural Noises in Recommender Systems". Algorithms 16, n.º 5 (27 de abril de 2023): 228. http://dx.doi.org/10.3390/a16050228.
Texto completoCui, Zeyu, Feng Yu, Shu Wu, Qiang Liu y Liang Wang. "Disentangled Item Representation for Recommender Systems". ACM Transactions on Intelligent Systems and Technology 12, n.º 2 (marzo de 2021): 1–20. http://dx.doi.org/10.1145/3445811.
Texto completoVaidhehi, V. y R. Suchithra. "A Systematic Review of Recommender Systems in Education". International Journal of Engineering & Technology 7, n.º 3.4 (25 de junio de 2018): 188. http://dx.doi.org/10.14419/ijet.v7i3.4.16771.
Texto completoHawashin, Bilal, Darah Aqel, Shadi Alzubi y Mohammad Elbes. "Improving Recommender Systems Using Co-Appearing and Semantically Correlated User Interests". Recent Advances in Computer Science and Communications 13, n.º 2 (3 de junio de 2020): 240–47. http://dx.doi.org/10.2174/2213275912666190115162311.
Texto completoTorres, Nicolás y Marcelo Mendoza. "Clustering Approaches for Top-k Recommender Systems". International Journal on Artificial Intelligence Tools 28, n.º 05 (agosto de 2019): 1950019. http://dx.doi.org/10.1142/s0218213019500192.
Texto completoThanh, Tran Thi. "A STUDY ON MOVIE RECOMMENDER SYSTEMS BASED ON WORDPRESS PLATFORM". International Journal of Engineering Technologies and Management Research 7, n.º 6 (3 de julio de 2020): 152–55. http://dx.doi.org/10.29121/ijetmr.v7.i6.2020.709.
Texto completoBen-Porat, Omer, Lee Cohen, Liu Leqi, Zachary C. Lipton y Yishay Mansour. "Modeling Attrition in Recommender Systems with Departing Bandits". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 6 (28 de junio de 2022): 6072–79. http://dx.doi.org/10.1609/aaai.v36i6.20554.
Texto completoLin, Dongding, Jian Wang y Wenjie Li. "COLA: Improving Conversational Recommender Systems by Collaborative Augmentation". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 4 (26 de junio de 2023): 4462–70. http://dx.doi.org/10.1609/aaai.v37i4.25567.
Texto completoLuo, Xin, Mengchu Zhou, Shuai Li, Yunni Xia, Zhuhong You, Qingsheng Zhu y Hareton Leung. "An Efficient Second-Order Approach to Factorize Sparse Matrices in Recommender Systems". IEEE Transactions on Industrial Informatics 11, n.º 4 (agosto de 2015): 946–56. http://dx.doi.org/10.1109/tii.2015.2443723.
Texto completoIndira, K. y M. K. Kavithadevi. "Efficient Machine Learning Model for Movie Recommender Systems Using Multi-Cloud Environment". Mobile Networks and Applications 24, n.º 6 (16 de octubre de 2019): 1872–82. http://dx.doi.org/10.1007/s11036-019-01387-4.
Texto completoBoudaa, Boudjemaa, Djamila Figuir, Slimane Hammoudi y Sidi mohamed Benslimane. "DATAtourist". International Journal of Decision Support System Technology 13, n.º 2 (abril de 2021): 62–84. http://dx.doi.org/10.4018/ijdsst.2021040104.
Texto completoGhosh, Aritra, Saayan Mitra y Andrew Lan. "DiPS: Differentiable Policy for Sketching in Recommender Systems". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 6 (28 de junio de 2022): 6703–12. http://dx.doi.org/10.1609/aaai.v36i6.20625.
Texto completoBatra, Priya, Anukriti Singh y T. S. Mahesh. "Efficient Characterization of Quantum Evolutions via a Recommender System". Quantum 5 (6 de diciembre de 2021): 598. http://dx.doi.org/10.22331/q-2021-12-06-598.
Texto completoSarwat, Mohamed, Justin J. Levandoski, Ahmed Eldawy y Mohamed F. Mokbel. "LARS*: An Efficient and Scalable Location-Aware Recommender System". IEEE Transactions on Knowledge and Data Engineering 26, n.º 6 (junio de 2014): 1384–99. http://dx.doi.org/10.1109/tkde.2013.29.
Texto completoWang, Zehong, Jianhua Liu, Shigen Shen y Minglu Li. "Restaurant Recommendation in Vehicle Context Based on Prediction of Traffic Conditions". International Journal of Pattern Recognition and Artificial Intelligence 35, n.º 10 (agosto de 2021): 2159044. http://dx.doi.org/10.1142/s0218001421590448.
Texto completoJeong, Hanjo y Kyung Jin CHA. "An Efficient MapReduce-Based Parallel Processing Framework for User-Based Collaborative Filtering". Symmetry 11, n.º 6 (3 de junio de 2019): 748. http://dx.doi.org/10.3390/sym11060748.
Texto completoStarke, Alain, Martijn Willemsen y Chris Snijders. "Promoting Energy-Efficient Behavior by Depicting Social Norms in a Recommender Interface". ACM Transactions on Interactive Intelligent Systems 11, n.º 3-4 (31 de diciembre de 2021): 1–32. http://dx.doi.org/10.1145/3460005.
Texto completoDo, Virginie, Sam Corbett-Davies, Jamal Atif y Nicolas Usunier. "Online Certification of Preference-Based Fairness for Personalized Recommender Systems". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 6 (28 de junio de 2022): 6532–40. http://dx.doi.org/10.1609/aaai.v36i6.20606.
Texto completoBouni, Mohamed, Badr Hssina, Khadija Douzi y Samira Douzi. "Towards an Efficient Recommender Systems in Smart Agriculture: A deep reinforcement learning approach". Procedia Computer Science 203 (2022): 825–30. http://dx.doi.org/10.1016/j.procs.2022.07.124.
Texto completoWang, Pengyu, Yong Wang, Leo Yu Zhang y Hong Zhu. "An effective and efficient fuzzy approach for managing natural noise in recommender systems". Information Sciences 570 (septiembre de 2021): 623–37. http://dx.doi.org/10.1016/j.ins.2021.05.002.
Texto completoDrif, Ahlem y Hocine Cherifi. "MIGAN: Mutual-Interaction Graph Attention Network for Collaborative Filtering". Entropy 24, n.º 8 (5 de agosto de 2022): 1084. http://dx.doi.org/10.3390/e24081084.
Texto completoLiu, Lewis y Kun Zhao. "Asynchronous Stochastic Gradient Descent for Extreme-Scale Recommender Systems". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 1 (18 de mayo de 2021): 328–35. http://dx.doi.org/10.1609/aaai.v35i1.16108.
Texto completoChicaiza, Janneth y Priscila Valdiviezo-Diaz. "A Comprehensive Survey of Knowledge Graph-Based Recommender Systems: Technologies, Development, and Contributions". Information 12, n.º 6 (28 de mayo de 2021): 232. http://dx.doi.org/10.3390/info12060232.
Texto completoStitini, O., S. Kaloun y O. Bencharef. "INVESTIGATING DIFFERENT SIMILARITY METRICS USED IN VARIOUS RECOMMENDER SYSTEMS TYPES: SCENARIO CASES". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W3-2022 (2 de diciembre de 2022): 187–93. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w3-2022-187-2022.
Texto completoYan, Surong, Kwei-Jay Lin, Xiaolin Zheng, Wenyu Zhang y Xiaoqing Feng. "An Approach for Building Efficient and Accurate Social Recommender Systems Using Individual Relationship Networks". IEEE Transactions on Knowledge and Data Engineering 29, n.º 10 (1 de octubre de 2017): 2086–99. http://dx.doi.org/10.1109/tkde.2017.2717984.
Texto completoXin Luo, Mengchu Zhou, Yunni Xia y Qingsheng Zhu. "An Efficient Non-Negative Matrix-Factorization-Based Approach to Collaborative Filtering for Recommender Systems". IEEE Transactions on Industrial Informatics 10, n.º 2 (mayo de 2014): 1273–84. http://dx.doi.org/10.1109/tii.2014.2308433.
Texto completoIbrahim, Muhammad y Imran Bajwa. "Design and Application of a Multi-Variant Expert System Using Apache Hadoop Framework". Sustainability 10, n.º 11 (19 de noviembre de 2018): 4280. http://dx.doi.org/10.3390/su10114280.
Texto completoMaazouzi, Faiz, Hafed Zarzour y Yaser Jararweh. "An Effective Recommender System Based on Clustering Technique for TED Talks". International Journal of Information Technology and Web Engineering 15, n.º 1 (enero de 2020): 35–51. http://dx.doi.org/10.4018/ijitwe.2020010103.
Texto completoLiu, Hanwen, Huaizhen Kou, Chao Yan y Lianyong Qi. "Keywords-Driven and Popularity-Aware Paper Recommendation Based on Undirected Paper Citation Graph". Complexity 2020 (24 de abril de 2020): 1–15. http://dx.doi.org/10.1155/2020/2085638.
Texto completonarayan, subhashini. "Multilayer Perceptron with Auto encoder enabled Deep Learning model for Recommender Systems". Future Computing and Informatics Journal 5, n.º 2 (30 de diciembre de 2020): 96–116. http://dx.doi.org/10.54623/fue.fcij.5.2.3.
Texto completoLiu, Hai, Chao Zheng, Duantengchuan Li, Xiaoxuan Shen, Ke Lin, Jiazhang Wang, Zhen Zhang, Zhaoli Zhang y Neal N. Xiong. "EDMF: Efficient Deep Matrix Factorization With Review Feature Learning for Industrial Recommender System". IEEE Transactions on Industrial Informatics 18, n.º 7 (julio de 2022): 4361–71. http://dx.doi.org/10.1109/tii.2021.3128240.
Texto completoChen, Jiawei, Chengquan Jiang, Can Wang, Sheng Zhou, Yan Feng, Chun Chen, Martin Ester y Xiangnan He. "CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation". ACM Transactions on Information Systems 39, n.º 3 (22 de mayo de 2021): 1–24. http://dx.doi.org/10.1145/3450289.
Texto completoNadimi-Shahraki, Mohammad-Hossein y Mozhde Bahadorpour. "Cold-start Problem in Collaborative Recommender Systems: Efficient Methods Based on Ask-to-rate Technique". Journal of Computing and Information Technology 22, n.º 2 (2014): 105. http://dx.doi.org/10.2498/cit.1002223.
Texto completoWei, Lingtao. "Communication Efficient Federated Personalized Recommendation". Frontiers in Computing and Intelligent Systems 2, n.º 3 (13 de febrero de 2023): 63–67. http://dx.doi.org/10.54097/fcis.v2i3.5214.
Texto completoRrmoku, Korab, Besnik Selimi y Lule Ahmedi. "Provenance and social network analysis for recommender systems: a literature review". International Journal of Electrical and Computer Engineering (IJECE) 12, n.º 5 (1 de octubre de 2022): 5383. http://dx.doi.org/10.11591/ijece.v12i5.pp5383-5392.
Texto completoCho, Gyungah, Pyoung-seop Shim y Jaekwang Kim. "Explainable B2B Recommender System for Potential Customer Prediction Using KGAT". Electronics 12, n.º 17 (22 de agosto de 2023): 3536. http://dx.doi.org/10.3390/electronics12173536.
Texto completoKhan, Zeshan Aslam, Naveed Ishtiaq Chaudhary, Waqar Ali Abbasi, Sai Ho Ling y Muhammad Asif Zahoor Raja. "Design of Confidence-Integrated Denoising Auto-Encoder for Personalized Top-N Recommender Systems". Mathematics 11, n.º 3 (2 de febrero de 2023): 761. http://dx.doi.org/10.3390/math11030761.
Texto completoIvanova, M. I. "Recommender systems in the public administration: methodological overview and conceptualization". Journal of Law and Administration 17, n.º 2 (16 de julio de 2021): 61–69. http://dx.doi.org/10.24833/2073-8420-2021-2-59-61-69.
Texto completoAgarwal, Vipul y Vijayalakshmi A. "Recommender system for surplus stock clearance". International Journal of Electrical and Computer Engineering (IJECE) 9, n.º 5 (1 de octubre de 2019): 3813. http://dx.doi.org/10.11591/ijece.v9i5.pp3813-3821.
Texto completoWang, Xixian, Xiaoming Wang, Binrui Huang, Mingzhan Dai y Jianwei Li. "Efficient Personalized Recommendation Based on Federated Learning with Similarity Ciphertext Calculation". Security and Communication Networks 2022 (16 de septiembre de 2022): 1–15. http://dx.doi.org/10.1155/2022/8607234.
Texto completoLe, Quang-Hung, Son-Lam Vu, Thi-Kim-Phuong Nguyen y Thi-Xinh Le. "A State-of-the-Art Survey on Context-Aware Recommender Systems and Applications". International Journal of Knowledge and Systems Science 12, n.º 3 (julio de 2021): 1–20. http://dx.doi.org/10.4018/ijkss.2021070101.
Texto completoEt. al., Geluvaraj B,. "AMatrix factorization technique using parameter tuning of singular value decomposition for Recommender Systems". Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, n.º 2 (10 de abril de 2021): 3313–19. http://dx.doi.org/10.17762/turcomat.v12i2.2390.
Texto completoNittu, Goutham, Singh Karan, Banda Latha, Sharma Purushottam, Verma Chaman y Goyal S. B. "ShAD-SEF: An Efficient Model for Shilling Attack Detection using Stacking Ensemble Framework in Recommender Systems". International Journal of Performability Engineering 19, n.º 5 (2023): 291. http://dx.doi.org/10.23940/ijpe.23.05.p1.291302.
Texto completoHu, Kerui, Lemiao Qiu, Shuyou Zhang, Zili Wang, Naiyu Fang y Huifang Zhou. "A novel neighbor selection scheme based on dynamic evaluation towards recommender systems". Science Progress 106, n.º 2 (abril de 2023): 003685042311800. http://dx.doi.org/10.1177/00368504231180090.
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