Expert list-wise ranking method based on sparse learning

Author:

Wang Liren,Yu Zhengtao,Jin Taisong,Li Xianhui,Gao Shengxiang

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference23 articles.

1. C. Macdonald, B. He, V. Plachouras, et al., University of Glasgow at TREC 2005: Experiments in Terabyte and Enterprise Tracks with Terrier, in: Proceeding of the 14th Text REtrieval Conference (TREC2005), Gaithersburg, USA, 2005.

2. Y. Fu, W. Yu, Y. Li, et al., THUIR at TREC 2005. Enterprise Track, in: Proceedings of the 14th Text Etrieval Conference (TREC2005), Gaithersburg, USA, 2005.

3. Yi Fang, Luo Si, Discriminative models of integrating document evidence and document-candidate associations for expert search, in: Proceeding of the 33rd international ACM SIGIR, Geneva, Switzerland, 2010, pp. 683–690.

4. T. Joachims, Optimizing search engines using click through data, in: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Edmonton, Alberta, Canada, 2002, pp. 133–142.

5. An efficient boosting Algorithm for combining preference;Freund;J. Mach. Learn. Res.,2003

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