图书情报工作 ›› 2014, Vol. 58 ›› Issue (15): 135-141.DOI: 10.13266/j.issn.0252-3116.2014.15.020

• 知识组织 • 上一篇    下一篇

基于特征项的文献共现网络在学术信息检索中的应用

丁洁, 王曰芬   

  1. 南京理工大学经济管理学院
  • 收稿日期:2014-05-19 修回日期:2014-07-06 出版日期:2014-08-05 发布日期:2014-08-05
  • 通讯作者: 王曰芬,南京理工大学经济管理学院教授,博士生导师,通讯作者,E-mail:yuefen163@163.com
  • 作者简介:丁洁,南京理工大学经济管理学院硕士研究生
  • 基金资助:

    本文系国家自然科学基金资助项目“新研究领域科学文献传播网络成长及对传播效果影响研究”(项目编号:71373124)研究成果之一。

Technologies and Applications of Literature Co-occurrence Network Based on Characteristic Terms in Academic Information Retrieval

Ding Jie, Wang Yuefen   

  1. School of Economics and Management, Nanjing University of Science & Technology, Nanjing 210094
  • Received:2014-05-19 Revised:2014-07-06 Online:2014-08-05 Published:2014-08-05

摘要:

在综合国内学术信息检索服务的现状和现有理论方法研究的基础上,以检索词推荐为研究对象,构建基于文献特征项共现网络的学术信息检索词推荐模型。模型包括基础文献存储模块、文献特征项抽取模块、文献特征项共现网络预处理模块、基于特征项的文献检索模块及检索词服务前端5个部分。利用实验验证基于特征项的共现网络用于检索词推荐的可行性,结果表明推荐模型结果与各检索项的检索词更具有相关性,推荐质量较好。

关键词: 检索词推荐, 推荐模型, 共现分析, 学术信息检索, 科技文献

Abstract:

After analyzing the present situation of the domestic academic information retrieval services and research status at home and abroad, a digital academic information query suggestion recommendation model based on co-occurrence analysis was developed, which includes the basic literatures storage module, the literatures feature item extraction module, the literatures feature co-occurrence network preprocessing module, the literature search module based on feature item and the front-end of search term services. An experiment was done to verify the model. The research showed that the academic information query suggestion recommendation model based on co-occurrence analysis of literature characteristic terms achieved better recommendation quality.

Key words: query suggestion, recommendation model, co-occurrence analysis, academic information retrieval, scientific literature

中图分类号: