山东科学 ›› 2019, Vol. 32 ›› Issue (2): 137-142.doi: 10.3976/j.issn.1002-4026.2019.02.018

• 其他研究论文 • 上一篇    

一种基于知识粒度的关键词提取方法

杨淑棉1,刘剑2   

  1. 1. 齐鲁工业大学(山东省科学院),山东省计算中心(国家超级计算济南中心),山东省计算机网络重点实验室,山东 济南 250014; 2. 济南高新区齐鲁软件园发展中心,山东 济南 250101
  • 收稿日期:2018-04-17 出版日期:2019-04-20 发布日期:2019-04-02
  • 作者简介:杨淑棉(1978—),女,副研究员,研究方向为计算机取证、网络信息安全。E-mail:yangshm@sdas.org
  • 基金资助:
    山东省自然科学基金(ZR2016YL011)

A keyword extraction method based on knowledge granularity

YANG Shu-mian1, LIU Jian2   

  1. 1. Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center (National Supercomputer Center in Jinan),Qilu University of Technology(Shandong Academy of Sciences),Jinan 250014, China; 2. Qilu Soft Park Development Center, Jinan 250101,China
  • Received:2018-04-17 Online:2019-04-20 Published:2019-04-02

摘要: 使用粗糙集中的等价关系来刻画粒度,粗糙集结合粒度计算方法,给出信息决策表的粒度表示,并将信息决策表中的属性重要度值作为启发信息,在相对约简的个数组合上进行Tabu搜索。此方法可避免无用的属性入选,有效去除可省属性及缩减搜索空间,提高了算法的高效性。

关键词: 知识粒, 重要度值, 粗糙集, 文本表示, 启发式信息

Abstract: In this paper, granularity was described by utilizing the equivalence relation in Rough sets, whose expression in information system and decision table was given by combining rough set with granularity calculation method. And using the attribute importance value in information decision table as heuristic information, Tabu search was carried out on the combination of relative reduction numbers. This method can avoid useless attributes selection, effectively wipe off attributes that can be omitted and reduce the search space, so as to ensure the efficiency of the algorithm.

Key words: knowledge granularity, importance value, rough set, text expression, heuristic information

中图分类号: 

  • TP393