Results 21 to 30 of about 1,101,099 (365)
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems [PDF]
The Web Conference, 2020 Learning effective feature crosses is the key behind building recommender systems. However, the sparse and large feature space requires exhaustive search to identify effective crosses.
Ruoxi Wang +6 more
semanticscholar +1 more source
PeerRank: Robust Learning to Rank With Peer Loss Over Noisy Labels
IEEE Access, 2022 User-generated data are extensively utilized in learning to rank as they are easy to collect and up-to-date. However, the data inevitably contain noisy labels attributed to users’ annotation mistakes, lack of domain knowledge, system failure, etc.,
Xin Wu, Qing Liu, Jiarui Qin, Yong Yu
doaj +1 more source
Differentiable Ranking Metric Using Relaxed Sorting for Top-K Recommendation
IEEE Access, 2021 Most recommenders generate recommendations for a user by computing the preference score of items, sorting the items according to the score, and filtering top- $K$ -items of high scores.
Hyunsung Lee +4 more
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RankEval: Evaluation and investigation of ranking models
SoftwareX, 2020 RankEval is a Python open-source tool for the analysis and evaluation of ranking models based on ensembles of decision trees. Learning-to-Rank (LtR) approaches that generate tree-ensembles are considered the most effective solution for difficult ranking ...
Claudio Lucchese +4 more
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Maximizing Marginal Fairness for Dynamic Learning to Rank [PDF]
The Web Conference, 2021 Rankings, especially those in search and recommendation systems, often determine how people access information and how information is exposed to people. Therefore, how to balance the relevance and fairness of information exposure is considered as one of ...
Tao Yang, Qingyao Ai
semanticscholar +1 more source
Learning to rank spatio-temporal event hotspots
Crime Science, 2020 Background Crime, traffic accidents, terrorist attacks, and other space-time random events are unevenly distributed in space and time. In the case of crime, hotspot and other proactive policing programs aim to focus limited resources at the highest risk ...
George Mohler +3 more
doaj +1 more source
Effective Learning to Rank Persian Web Content [PDF]
Journal of Information Technology Management, 2019 Persian language is one of the most widely used languages in the Web environment. Hence, the Persian Web includes invaluable information that is required to be retrieved effectively.
Amir Hosein Keyhanipour
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Answering questions by learning to rank - Learning to rank by answering questions [PDF]
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019 Presented at EMNLP 2019; 10 pages, 5 ...
George Sebastian Pirtoaca +2 more
openaire +3 more sources
Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach
AAAI Conference on Artificial Intelligence, 2021 Quantitative trading and investment decision making are intricate financial tasks that rely on accurate stock selection. Despite advances in deep learning that have made significant progress in the complex and highly stochastic stock prediction problem ...
Ramit Sawhney +4 more
semanticscholar +1 more source
Journal of King Saud University: Computer and Information Sciences, 2020 This paper proposed a new method for learning to rank documents using enumerative feature subsetting in the presence of the implicit user feedback of the various classes of users.
Mohd Wazih Ahmad +2 more
doaj +1 more source