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Interactive preference analysis: A reinforcement learning framework. (2024). Hu, Xiao ; Kang, Siqin ; Zhu, Shaokeng ; Ren, Long.
In: European Journal of Operational Research.
RePEc:eee:ejores:v:319:y:2024:i:3:p:983-998.

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  1. Abbas, K. ; Afaq, M. ; Ahmed Khan, T. ; Song, W.-C. A blockchain and machine learning-based drug supply chain management and recommendation system for smart pharmaceutical industry. 2020 Electronics. 9 852-
    Paper not yet in RePEc: Add citation now
  2. Adeniyi, D.A. ; Wei, Z. ; Yongquan, Y. Automated web usage data mining and recommendation system using K-Nearest Neighbor (KNN) classification method. 2016 Applied Computing and Informatics. 12 90-108
    Paper not yet in RePEc: Add citation now
  3. Alsabah, H. ; Capponi, A. ; Ruiz Lacedelli, O. ; Stern, M. Robo-advising: Learning investors’ risk preferences via portfolio choices. 2021 Journal of Financial Econometrics. 19 369-392

  4. Amari, S.-i. Backpropagation and stochastic gradient descent method. 1993 Neurocomputing. 5 185-196
    Paper not yet in RePEc: Add citation now
  5. Amir, N. ; Jabeen, F. ; Ali, Z. ; Ullah, I. ; Jan, A.U. ; Kefalas, P. On the current state of deep learning for news recommendation. 2023 Artificial Intelligence Review. 56 1101-1144
    Paper not yet in RePEc: Add citation now
  6. Baković, J. Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis. 2023 University of Rijeka. Faculty of Maritime Studies, Rijeka. Department of:
    Paper not yet in RePEc: Add citation now
  7. Bentéjac, C. ; Csörgő, A. ; Martínez-Muñoz, G. A comparative analysis of gradient boosting algorithms. 2021 Artificial Intelligence Review. 54 1937-1967
    Paper not yet in RePEc: Add citation now
  8. Breffle, W.S. ; Morey, E.R. ; Thacher, J.A. A joint latent-class model: Combining likert-scale preference statements with choice data to harvest preference heterogeneity. 2011 Environmental and Resource Economics. 50 83-110

  9. Brenner, L. ; Meyll, T. Robo-advisors: A substitute for human financial advice?. 2020 Journal of Behavioral and Experimental Finance. 25 -

  10. Brodén, B., Hammar, M., Nilsson, B. J., & Paraschakis, D. (2018). Ensemble recommendations via Thompson sampling: An experimental study within e-commerce. In 23rd international conference on intelligent user interfaces (pp. 19–29).
    Paper not yet in RePEc: Add citation now
  11. Capponi, A. ; Olafsson, S. ; Zariphopoulou, T. Personalized robo-advising: Enhancing investment through client interaction. 2022 Management Science. 68 2485-2512

  12. Chakrabarti, D. ; Kumar, R. ; Radlinski, F. ; Upfal, E. Mortal multi-armed bandits. 2008 En : . :
    Paper not yet in RePEc: Add citation now
  13. Chang, J. ; Zhang, C. ; Hui, Y. ; Leng, D. ; Niu, Y. ; Song, Y. PEPNet: Parameter and embedding personalized network for infusing with personalized prior information. 2023 :
    Paper not yet in RePEc: Add citation now
  14. Chang, Y.-H. ; Lin, H.-T. Pairwise regression with upper confidence bound for contextual bandit with multiple actions. 2013 En : 2013 conference on technologies and applications of artificial intelligence. IEEE:
    Paper not yet in RePEc: Add citation now
  15. Chapelle, O. ; Li, L. An empirical evaluation of Thompson sampling. 2011 En : . :
    Paper not yet in RePEc: Add citation now
  16. Chen, J. ; Xiong, J. ; Chen, G. ; Liu, X. ; Yan, P. ; Jiang, H. Optimal instant discounts of multiple ride options at a ride-hailing aggregator. 2024 European Journal of Operational Research. 314 718-734

  17. Chen, L. ; Xu, Z. A new fuzzy programming method to derive the priority vector from an interval reciprocal comparison matrix. 2015 Information Sciences. 316 148-162
    Paper not yet in RePEc: Add citation now
  18. Chou, K.-C. ; Lin, H.-T. ; Chiang, C.-K. ; Lu, C.-J. Pseudo-reward algorithms for contextual bandits with linear payoff functions. 2015 En : Asian conference on machine learning. PMLR:
    Paper not yet in RePEc: Add citation now
  19. Chowdhury, S.R. ; Gopalan, A. On kernelized multi-armed bandits. 2017 En : International conference on machine learning. PMLR:
    Paper not yet in RePEc: Add citation now
  20. Chu, W. ; Li, L. ; Reyzin, L. ; Schapire, R. Contextual bandits with linear payoff functions. 2011 En : Proceedings of the fourteenth international conference on artificial intelligence and statistics. JMLR Workshop and Conference Proceedings:
    Paper not yet in RePEc: Add citation now
  21. D’Acunto, F. ; Rossi, A.G. Robo-advice: Transforming households into rational economic agents. 2023 Annual Review of Financial Economics. 15 543-563

  22. De Bock, K.W. ; Coussement, K. ; De Caigny, A. ; Slowiński, R. ; Baesens, B. ; Boute, R.N. Explainable AI for operational research: A defining framework, methods, applications, and a research agenda. 2023 European Journal of Operational Research. -

  23. Dega, S. ; Dietrich, P. ; Schrön, M. ; Paasche, H. Probabilistic prediction by means of the propagation of response variable uncertainty through a Monte Carlo approach in regression random forest: Application to soil moisture regionalization. 2023 Frontiers in Environmental Science. 11 -
    Paper not yet in RePEc: Add citation now
  24. Deveikyte, J. ; Geman, H. ; Piccari, C. ; Provetti, A. A sentiment analysis approach to the prediction of market volatility. 2022 Frontiers in Artificial Intelligence. 5 -
    Paper not yet in RePEc: Add citation now
  25. Dybvig, P.H. ; Farnsworth, H.K. ; Carpenter, J.N. Portfolio performance and agency. 2010 The Review of Financial Studies. 23 1-23

  26. Elena, G. ; Milos, K. ; Eugene, I. Survey of multiarmed bandit algorithms applied to recommendation systems. 2021 International Journal of Open Information Technologies. 9 12-27
    Paper not yet in RePEc: Add citation now
  27. Evangelopoulos, N. ; Zhang, X. ; Prybutok, V.R. Latent semantic analysis: Five methodological recommendations. 2012 European Journal of Information Systems. 21 70-86

  28. Fischer, T. ; Krauss, C. Deep learning with long short-term memory networks for financial market predictions. 2018 European Journal of Operational Research. 270 654-669

  29. Gao, C. ; Wang, S. ; Li, S. ; Chen, J. ; He, X. ; Lei, W. CIRS: Bursting filter bubbles by counterfactual interactive recommender system. 2023 ACM Transactions on Information Systems. 42 1-27
    Paper not yet in RePEc: Add citation now
  30. Gentile, C. ; Li, S. ; Zappella, G. Online clustering of bandits. 2014 En : International conference on machine learning. PMLR:
    Paper not yet in RePEc: Add citation now
  31. Gong, Z.-W. Least-square method to priority of the fuzzy preference relations with incomplete information. 2008 International Journal of Approximate Reasoning. 47 258-264
    Paper not yet in RePEc: Add citation now
  32. Guo, L. ; Zhang, J. ; Chen, T. ; Wang, X. ; Yin, H. Reinforcement learning-enhanced shared-account cross-domain sequential recommendation. 2022 IEEE Transactions on Knowledge and Data Engineering. -
    Paper not yet in RePEc: Add citation now
  33. Gurrea-Martinez, A. ; Wan, W.Y. The promises and perils of robo-advisers. 2023 En : Artificial intelligence in finance. Edward Elgar Publishing:
    Paper not yet in RePEc: Add citation now
  34. Gutowski, N. ; Amghar, T. ; Camp, O. ; Chhel, F. Gorthaur-EXP3: Bandit-based selection from a portfolio of recommendation algorithms balancing the accuracy-diversity dilemma. 2021 Information Sciences. 546 378-396
    Paper not yet in RePEc: Add citation now
  35. Henderi, H. ; Wahyuningsih, T. ; Rahwanto, E. Comparison of min-max normalization and Z-score normalization in the k-Nearest Neighbor (kNN) algorithm to test the accuracy of types of breast cancer. 2021 International Journal of Informatics and Information Systems. 4 13-20
    Paper not yet in RePEc: Add citation now
  36. Hou, Y.-e. ; Gu, W. ; Dong, W. ; Dang, L. A deep reinforcement learning real-time recommendation model based on long and short-term preference. 2023 International Journal of Computational Intelligence Systems. 16 4-
    Paper not yet in RePEc: Add citation now
  37. Hu, X. ; Chen, Y. ; Ren, L. ; Xu, Z. Investor preference analysis: An online optimization approach with missing information. 2023 Information Sciences. 633 27-40
    Paper not yet in RePEc: Add citation now
  38. Jin, J. ; Cui, T. ; Bai, R. ; Qu, R. Container port truck dispatching optimization using Real2Sim based deep reinforcement learning. 2024 European Journal of Operational Research. 315 161-175

  39. Kallestad, J. ; Hasibi, R. ; Hemmati, A. ; Sörensen, K. A general deep reinforcement learning hyperheuristic framework for solving combinatorial optimization problems. 2023 European Journal of Operational Research. 309 446-468

  40. Ko, H. ; Lee, S. ; Park, Y. ; Choi, A. A survey of recommendation systems: recommendation models, techniques, and application fields. 2022 Electronics. 11 141-
    Paper not yet in RePEc: Add citation now
  41. Komiyama, J. ; Honda, J. ; Nakagawa, H. Optimal regret analysis of Thompson sampling in stochastic multi-armed bandit problem with multiple plays. 2015 En : International conference on machine learning. PMLR:
    Paper not yet in RePEc: Add citation now
  42. Koren, Y. ; Bell, R. ; Volinsky, C. Matrix factorization techniques for recommender systems. 2009 Computer. 42 30-37
    Paper not yet in RePEc: Add citation now
  43. Kou, G. ; Lin, C. A cosine maximization method for the priority vector derivation in AHP. 2014 European Journal of Operational Research. 235 225-232

  44. Kuleshov, V. ; Precup, D. Algorithms for multi-armed bandit problems. 2014 :
    Paper not yet in RePEc: Add citation now
  45. Lee, M.-C. ; Chang, J.-W. ; Hung, J.C. ; Chen, B.-L. Exploring the effectiveness of deep neural networks with technical analysis applied to stock market prediction. 2021 Computer Science and Information Systems. 18 401-418
    Paper not yet in RePEc: Add citation now
  46. Li, L. ; Wang, J. ; Li, X. Efficiency analysis of machine learning intelligent investment based on K-means algorithm. 2020 Ieee Access. 8 147463-147470
    Paper not yet in RePEc: Add citation now
  47. Li, X. ; Wu, Z. Reputation entrenchment or risk minimization? Early stop and investor-manager agency conflict in fund management. 2008 The Journal of Risk Finance. 9 125-150

  48. Lipovetsky, S. Priority vector estimation: Consistency, compatibility, precision. 2020 International Journal of the Analytic Hierarchy Process. 12 -
    Paper not yet in RePEc: Add citation now
  49. Loukili, M. ; Messaoudi, F. ; El Ghazi, M. Machine learning based recommender system for e-commerce. 2023 IAES International Journal of Artificial Intelligence. 12 1803-1811
    Paper not yet in RePEc: Add citation now
  50. Maiti, A. ; Patil, V. ; Khan, A. Multi-armed bandits with bounded arm-memory: Near-optimal guarantees for best-arm identification and regret minimization. 2021 Advances in Neural Information Processing Systems. 34 19553-19565
    Paper not yet in RePEc: Add citation now
  51. McInerney, J., Lacker, B., Hansen, S., Higley, K., Bouchard, H., Gruson, A., et al. (2018). Explore, exploit, and explain: Personalizing explainable recommendations with bandits. In Proceedings of the 12th ACM conference on recommender systems (pp. 31–39).
    Paper not yet in RePEc: Add citation now
  52. Mustapha, R. ; Soukaina, G. ; Mohammed, Q. ; Es-Sâadia, A. Towards an adaptive e-learning system based on deep learner profile, machine learning approach, and reinforcement learning. 2023 International Journal of Advanced Computer Science and Applications. 14 -
    Paper not yet in RePEc: Add citation now
  53. Neal, D. ; Warren, G. Long-term investing as an agency problem. 2015 :
    Paper not yet in RePEc: Add citation now
  54. Ni, J., Li, J., & McAuley, J. (2019). Justifying recommendations using distantly-labeled reviews and fine-grained aspects. In Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (pp. 188–197).
    Paper not yet in RePEc: Add citation now
  55. Ou-Yang, H. Optimal contracts in a continuous-time delegated portfolio management problem. 2003 The Review of Financial Studies. 16 173-208

  56. Peake, G. ; Wang, J. Explanation mining: Post hoc interpretability of latent factor models for recommendation systems. 2018 En : Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining. :
    Paper not yet in RePEc: Add citation now
  57. Qadeer, A. ; Rizvi, S.K.A. ; Ahmad, A. General assessment of behavioral preferences of investors: A qualitative study. 2021 Journal of Business & Economics. 13 35-43
    Paper not yet in RePEc: Add citation now
  58. Ren, L. ; Zhu, B. ; Xu, Z. Continuous exp strategy for consumer preference analysis based on online ratings. 2021 IEEE Transactions on Fuzzy Systems. 30 2621-2633
    Paper not yet in RePEc: Add citation now
  59. Ren, L. ; Zhu, B. ; Xu, Z. Data-driven fuzzy preference analysis from an optimization perspective. 2019 Fuzzy Sets and Systems. 377 85-101
    Paper not yet in RePEc: Add citation now
  60. Rendle, S., Gantner, Z., Freudenthaler, C., & Schmidt-Thieme, L. (2011). Fast context-aware recommendations with factorization machines. In Proceedings of the 34th international ACM SIGIR conference on research and development in information retrieval (pp. 635–644).
    Paper not yet in RePEc: Add citation now
  61. Roscher, R. ; Bohn, B. ; Duarte, M.F. ; Garcke, J. Explainable machine learning for scientific insights and discoveries. 2020 IEEE Access. 8 42200-42216
    Paper not yet in RePEc: Add citation now
  62. Sarwar, B. ; Karypis, G. ; Konstan, J. ; Riedl, J. Incremental singular value decomposition algorithms for highly scalable recommender systems. 2002 En : . Citeseer:
    Paper not yet in RePEc: Add citation now
  63. Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th international conference on world wide web (pp. 285–295).
    Paper not yet in RePEc: Add citation now
  64. Schafer, J.B. ; Frankowski, D. ; Herlocker, J. ; Sen, S. Collaborative filtering recommender systems. 2007 En : The adaptive web: methods and strategies of web personalization. Springer:
    Paper not yet in RePEc: Add citation now
  65. Scott, R.C. ; Horvath, P.A. On the direction of preference for moments of higher order than the variance. 1980 The Journal of Finance. 35 915-919

  66. Seng, D. ; Hancock, J.R. Fundamental analysis and the prediction of earnings. 2012 International Journal of Business and Management. 7 32-
    Paper not yet in RePEc: Add citation now
  67. Shahbazi, Z. ; Byun, Y.-C. Product recommendation based on content-based filtering using XGBoost classifier. 2019 International Journal of Advanced Science and Technology. 29 6979-6988
    Paper not yet in RePEc: Add citation now
  68. Sharma, L. ; Gera, A. A survey of recommendation system: Research challenges. 2013 International Journal of Engineering Trends and Technology (IJETT). 4 1989-1992
    Paper not yet in RePEc: Add citation now
  69. Shuvo, S.S. ; Yilmaz, Y. Home energy recommendation system (hers): A deep reinforcement learning method based on residents’ feedback and activity. 2022 IEEE Transactions on Smart Grid. 13 2812-2821
    Paper not yet in RePEc: Add citation now
  70. Singh, R.H. ; Maurya, S. ; Tripathi, T. ; Narula, T. ; Srivastav, G. Movie recommendation system using cosine similarity and KNN. 2020 International Journal of Engineering and Advanced Technology. 9 556-559
    Paper not yet in RePEc: Add citation now
  71. Slivkins, A. Introduction to multi-armed bandits. 2019 Foundations and Trends® in Machine Learning. 12 1-286
    Paper not yet in RePEc: Add citation now
  72. Sollich, P. Bayesian methods for support vector machines: Evidence and predictive class probabilities. 2002 Machine Learning. 46 21-52
    Paper not yet in RePEc: Add citation now
  73. Stoughton, N.M. Moral hazard and the portfolio management problem. 1993 The Journal of Finance. 48 2009-2028

  74. Van Meteren, R. ; Van Someren, M. Using content-based filtering for recommendation. 2000 En : . Barcelona:
    Paper not yet in RePEc: Add citation now
  75. Von Neumann, J. ; Morgenstern, O. Theory of games and economic behavior (60th anniversary commemorative edition). 2007 Princeton University Press:
    Paper not yet in RePEc: Add citation now
  76. Wang, J.-J. ; Jing, Y.-Y. ; Zhang, C.-F. ; Zhao, J.-H. Review on multi-criteria decision analysis aid in sustainable energy decision-making. 2009 Renewable and Sustainable Energy Reviews. 13 2263-2278

  77. Wang, X. ; Chen, Y. ; Yang, J. ; Wu, L. ; Wu, Z. ; Xie, X. A reinforcement learning framework for explainable recommendation. 2018 En : 2018 IEEE international conference on data mining. IEEE:
    Paper not yet in RePEc: Add citation now
  78. Xian, Y., Fu, Z., Muthukrishnan, S., De Melo, G., & Zhang, Y. (2019). Reinforcement knowledge graph reasoning for explainable recommendation. In Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval (pp. 285–294).
    Paper not yet in RePEc: Add citation now
  79. Xiong, Y. ; Liu, Y. ; Qian, Y. ; Jiang, Y. ; Chai, Y. ; Ling, H. Based recommendation under preference uncertainty: An asymmetric deep learning framework. 2024 European Journal of Operational Research. -

  80. Xu, Z. Goal programming models for obtaining the priority vector of incomplete fuzzy preference relation. 2004 International Journal of Approximate Reasoning. 36 261-270
    Paper not yet in RePEc: Add citation now
  81. Zenati, H. ; Bietti, A. ; Diemert, E. ; Mairal, J. ; Martin, M. ; Gaillard, P. Efficient kernelized UCB for contextual bandits. 2022 En : International conference on artificial intelligence and statistics. PMLR:
    Paper not yet in RePEc: Add citation now
  82. Zhang, H. Group decision making based on multiplicative consistent reciprocal preference relations. 2016 Fuzzy Sets & Systems. 282 31-46
    Paper not yet in RePEc: Add citation now
  83. Zhang, H.-R. ; Min, F. Three-way recommender systems based on random forests. 2016 Knowledge-Based Systems. 91 275-286
    Paper not yet in RePEc: Add citation now
  84. Zhang, W. ; Zhou, D. ; Li, L. ; Gu, Q. Neural Thompson sampling. 2020 :
    Paper not yet in RePEc: Add citation now
  85. Zhang, Y. ; Chen, X. Explainable recommendation: A survey and new perspectives. 2020 Foundations and Trends® in Information Retrieval. 14 1-101
    Paper not yet in RePEc: Add citation now
  86. Zhang, Y. ; Xu, Z. ; Wang, H. ; Liao, H. Consistency-based risk assessment with probabilistic linguistic preference relation. 2016 Applied Soft Computing. 49 817-833
    Paper not yet in RePEc: Add citation now
  87. Zhao, Z.-D. ; Shang, M.-S. User-based collaborative-filtering recommendation algorithms on hadoop. 2010 En : 2010 third international conference on knowledge discovery and data mining. IEEE:
    Paper not yet in RePEc: Add citation now
  88. Zhou, T. ; Wang, Y. ; Yan, L. ; Tan, Y. Spoiled for choice? personalized recommendation for healthcare decisions: A multiarmed bandit approach. 2023 Information Systems Research. 34 1493-1512

  89. Zhu, B. ; Xu, Z. A fuzzy linear programming method for group decision making with additive reciprocal fuzzy preference relations. 2014 Fuzzy Sets and Systems. 246 19-33
    Paper not yet in RePEc: Add citation now

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    RePEc:eee:ecolec:v:74:y:2012:i:c:p:130-144.

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  27. Protester or non-protester: a binary state? on the use (and non-use) of latent class models to analyse protesting in economic valuation. (2012). Meyerhoff, Jürgen ; Bartczak, Anna ; Liebe, Ulf.
    In: Australian Journal of Agricultural and Resource Economics.
    RePEc:ags:aareaj:211675.

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  28. Do Farmers Have Heterogeneous Preferences for the Environment and Does It Matter? A Latent-Class Approach to Explaining Field-Level Tillage Choices. (2012). Roe, Brian ; Irwin, Elena G. ; Konar, Avishek.
    In: 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington.
    RePEc:ags:aaea12:124629.

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