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Feature selection for ranking
2007
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '07
Ranking is a very important topic in information retrieval. While algorithms for learning ranking models have been intensively studied, this is not the case for feature selection, despite of its importance. The reality is that many feature selection methods used in classification are directly applied to ranking. We argue that because of the striking differences between ranking and classification, it is better to develop different feature selection methods for ranking. To this end, we propose a
doi:10.1145/1277741.1277811
dblp:conf/sigir/GengLQL07
fatcat:sbet6naxnvhsfm3cdnmsjpyqpy