匹配学习Learning to Match

关于匹配学习,李航老师在今年图灵诞辰100周年的一个简单报告中简要介绍了匹配学习的意义。李航老师今年总共做了4个关于learning to match的报告
第一个:Workshop on Algorithms for Modern Massive Data Sets. Stanford University. July 10–13, 2012
[pdf],[video]
题目:Large Scale Machine Learning for Query Document Matching in Web Search
主要介绍Query-Document的重新表示并进行match匹配,他的第三篇报告20120817 Learning to Match for Natural Language Processing and Information Retrieval yssnlp_2012
[pdf],其中多介绍了String Re-writing Kernel的内容。
第二篇报告是一篇tutorial,
[pdf],内容非常详细,需要深入了解的同学值得一读。

就当前实验室有限的系统资源来说值得注意学习的地方时,1:term容错校正;2:Phrase标识;3:相似问题匹配。这几方面有几篇参考文献需要细读。
1:Jiafeng Guo, Gu Xu, Hang Li, Xueqi Cheng. A Unified and Discriminative Model for Query Refinement. In Proceedings of the 31st Annual International ACM SIGIR Conference (SIGIR’08), 379-386, 2008.
[Pdf]
2:Ziqi Wang, Gu Xu, Hang Li and Ming Zhang, A Fast and Accurate Method for Approximate String Search, In Proceedings of the 49th Annual Meeting of Association for Computational Linguistics: Human Language Technologies (ACL-HLT’11), 52-61, 2011.
[Pdf]
3:Fan Bu, Hang Li, Xiaoyan Zhu, String Re-Writing Kernel, In Proceedings of the 50th Annual Meeting of Association for Computational Linguistics (ACL’12), to appear, 2012.
[Pdf]

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