ListBM: A Learning-to-Rank Method for XML Keyword Search

被引：0

作者：

Gao, Nmg ^{[1
]}

Deng, Zhi-Hong ^{[1
]}

Xiang, Yong-Qing ^{[1
]}

Hang, Yu ^{[1
]}

机构：

[1] Peking Univ, Sch Elect Engn & Comp Sci, Key Lab Machine Percept, Minist Educ, Beijing, Peoples R China

来源：

FOCUSED RETRIEVAL AND EVALUATION | 2010年 / 6203卷

关键词：

XML keyword learn-to-rank;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes Peking University s approach to the Ad Hoc Track In our first participation, results for all four tasks were submitted the Best In Context the Focused the Relevance In Context and the Thorough Based on retrieval method Okapi BM25 we Implement two different ranking methods NormaIBM25 and LearningBM25 according to different parameter settings Specially, the parameters used in LearningBM25 are learnt by a new learning method called ListBM The evaluation result shows that LearningBM25 is able to beat NormalBM25 in most tasks

引用

页码：81 / 87

页数：7

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