System Development & Application
|
193-197

Method of pruning decision tree model and block-wise to speed-up ranking candidate documents

Li Weijiang
Chang Wei
Yu Zhengtao
School of Information Engineering & Automation, Kunming University of Science & Technology, Kunming 650500, China

Abstract

The retrieval system uses learning to rank(LtR) algorithms to produce a ranking model from public available training sets. The time required reducing to retrieve data is an important research direction of the retrieval system. In order to reduce the retrieval time, this paper studied the pruning strategy of ranking model and cache. Using the redundancy characteristics of the decision tree and the cache, it proposed a pruning decision tree model and block-wise algorithm. Finally, this paper aimed to answer the question that whether it could improve the efficiency of the ranking model without affecting the effectiveness of model. Experiments on two publicly dataset show that the pruning decision tree model and block-wise algorithm can effectively reduce the scoring time per query.

Foundation Support

国家自然科学基金资助项目(61363045)
云南省自然科学基金重点资助项目(2013FA130)
科技部中青年科技创新领军人才资助项目(2014HE001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.05.0443
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 1
Section: System Development & Application
Pages: 193-197
Serial Number: 1001-3695(2020)01-040-0193-05

Publish History

[2020-01-05] Printed Article

Cite This Article

李卫疆, 常伟, 余正涛. 加快排序文档的剪枝决策树和分块方法 [J]. 计算机应用研究, 2020, 37 (1): 193-197. (Li Weijiang, Chang Wei, Yu Zhengtao. Method of pruning decision tree model and block-wise to speed-up ranking candidate documents [J]. Application Research of Computers, 2020, 37 (1): 193-197. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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