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Ensemble Ranking SVM for learning to rank
2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011This paper deals with the problem of learning to rank documents for information retrieval. Until now, Ranking SVM has been successfully used for learning to rank documents. The basic idea of Ranking SVM is to formalize learning to rank as a problem of binary classification on instance pairs and solve the problem using SVM.
Cheolkon Jung, Licheng Jiao, Yanbo Shen
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Collaborative Ranking with Ranking-Based Neighborhood
2013Recommendation system is a very important tool to help users to find what they are interested in on the web. In many commercial recommendation systems, only the top-K items are shown to users, and recommendation becomes a ranking task rather than a classical rating prediction task.
Chaosheng Fan, Zuoquan Lin
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From Cluster Ranking to Document Ranking
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022Egor Markovskiy +3 more
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Analysis of sustainability of Chinese cities based on network big data of city rankings
Ecological Indicators, 2021Jiakun Liu, Li Xing, Meixia Lin
exaly
Does conflict of interest distort global university rankings?
Higher Education, 2022Igor Chirikov
exaly