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现代图书情报技术  2016, Vol. 32 Issue (11): 82-93    DOI: 10.11925/infotech.1003-3513.2016.11.10
  应用论文 本期目录 | 过刊浏览 | 高级检索 |
科技查新中检索词智能抽取系统的设计与实现*
王培霞1,2,余海1,2,陈力1,2,王永吉1()
1中国科学院软件研究所 北京 100190
2中国科学院大学 北京 100049
Using Intelligent System to Extract Search Terms for Sci-Tech Novelty Retrieval
Wang Peixia1,2,Yu Hai1,2,Chen Li1,2,Wang Yongji1()
1Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
2University of Chinese Academy of Sciences, Beijing 100049, China
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摘要 

目的】解决科技查新领域检索词选择时的主观性强、手工工作量大、不规范、费时费力的问题。【应用背景】为了实现检索词抽取过程的自动化、智能化、规范化, 本文提出利用科技查新过程检出的实时相关语料作为领域知识的来源, 并对语料组成类型与关键词抽取效果之间的关系进行讨论。【方法】通过关键词抽取、领域特征扩展相结合的递进式迭代抽取方式实现科技查新领域检索词的智能抽取。【结果】通过与实际查新案例所采用的检索词对比, 发现使用本方法两次迭代后抽取10个检索词, 召回率达到80%。【结论】基于查新过程中检出文献构成的动态相关语料进行检索词的迭代抽取有助于快速、准确锁定绝大部分检索词, 提高检索的效率和效果。

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王培霞
余海
陈力
王永吉
关键词 科技查新检索词关键词抽取抽取网络爬虫    
Abstract

[Objective] This paper aims to identifying the search terms more effectively in sci-tech novelty retrieval, which could reduce the subjectivity, heavy workload, de-normalization and time-consuming issues facing the manual methods. [Context] We used the corpus generated by the sci-tech novelty retrieval as the source of domain knowledge to extract search terms. Then, we discussed the relationship between the corpus and the keyword extraction. [Methods] We proposed an incremental iterative method to extract keywords from the sci-tech novelty retrieval project with the help of domain feature expansion. [Results] Compared to search terms from the real world sci-tech novelty retrieval, the recall rates of the 10 search terms extracted by the new method reached 80%. [Conclusions] The proposed method could identify most keywords and then improve the efficiency and effectiveness of the novelty retrieval tasks.

Key wordsSci-Tech novelty retrieval    Search terms    extraction    Online crawler
收稿日期: 2016-07-28     
基金资助:*本文系国家自然科学基金项目“云计算环境下的隐蔽信道机理研究”(项目编号: 61170072)、国家自然科学基金青年科学基金项目“移动智能终端隐蔽信道机理研究”(项目编号: 61303057)和中国科学院、国家外国专家局创新团队国际合作项目“安全攸关软件理论和构造方法”的研究成果之一
引用本文:   
王培霞,余海,陈力,王永吉. 科技查新中检索词智能抽取系统的设计与实现*[J]. 现代图书情报技术, 2016, 32(11): 82-93.
Wang Peixia,Yu Hai,Chen Li,Wang Yongji. Using Intelligent System to Extract Search Terms for Sci-Tech Novelty Retrieval. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2016.11.10.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2016.11.10
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