學術資源整合系統-相關推薦

 
作者Yeh, Jen-Yuan;Tsai, Cheng-Jung
出版日期20201128
著作名稱Graph-based Feature Selection Method for Learning to Rank
會議論文集Proceedings of the 6th International Conference on Communication and Information Processing (ICCIP 2020)
會議名稱The 6th International Conference on Communication and Information Processing (ICCIP 2020)
會議地點Tokyo, Japan
國際性會議Y
其他資訊 https://doi.org/10.1145/3442555.3442567
主題資訊科學
關鍵字Learning to rank, Feature selection, Feature similarity graph, Spectral clustering, Biased PageRank, Information retrieval
摘要In this paper, a graph-based feature selection method for learning to rank, called FS-SCPR, is proposed. FS-SCPR models feature relationships as a graph and selects a subset of features that have minimum redundancy with each other and have maximum relevance to the ranking problem. For minimizing redundancy, FS-SCPR abandons redundant features which are those being grouped into the same cluster. For maximizing relevance, FS-SCPR greedily collects from each cluster a representative feature which is with high relevance to the ranking problem. This paper utilizes FS-SCPR as a preprocessor for determining discriminative and useful features and employs Ranking SVM to derive a ranking model for document retrieval with the selected features. The proposed approach is evaluated using the LETOR datasets and found to perform competitively when being compared to another feature selection method, GAS-E.
系統號NO000005893

Aug 20 2021 11:12:17
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