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