[1]康向平,苗夺谦.一种基于概念格的集值信息系统中的知识获取方法[J].智能系统学报编辑部,2016,11(3):287-293.[doi:10.11992/tis.201603055]
KANG Xiangping,MIAO Duoqian.A knowledge acquisition method based on concept latticein set-valued information systems[J].CAAI Transactions on Intelligent Systems,2016,11(3):287-293.[doi:10.11992/tis.201603055]
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KANG Xiangping,MIAO Duoqian.A knowledge acquisition method based on concept latticein set-valued information systems[J].CAAI Transactions on Intelligent Systems,2016,11(3):287-293.[doi:10.11992/tis.201603055]
一种基于概念格的集值信息系统中的知识获取方法
《智能系统学报》编辑部[ISSN 1673-4785/CN 23-1538/TP] 卷:
11
期数:
2016年第3期
页码:
287-293
栏目:
学术论文—机器感知与模式识别
出版日期:
2016-06-25
- Title:
- A knowledge acquisition method based on concept latticein set-valued information systems
- Keywords:
- rough set; concept lattice; set-valued information systems; tolerance relations; algebraic structure
- 分类号:
- TP18
- 摘要:
- 以集值信息系统为研究背景,以概念格为理论基础,提出了一种基于概念格的集值信息系统中的知识获取方法。该模型首先将复杂的集值信息系统转化为形式上更加简单的单值背景,然后借助概念格理论,重点探讨了基于相容关系的粒化模型和集值系统中的格代数结构,该代数结构可以将论域中的所有覆盖以格的形式有机结织起来。此外,探讨了集值信息系统中的约简、核等问题。本文有助于拓展概念格的应用范围,同时也为集值信息系统的分析和处理提供了一种有益思路。
- Abstract:
- The paper takes set-valued information systems as research background, proposes a knowledge acquisition method on the basis of concept lattice. The model can transforms a complicated set-valued information system into a simpler one-valued context, and then by means of concept lattice, emphasizes the granularity model based on tolerance relation and the algebra structure in the set-valued information system, where the algebraic structure can organize all covers in the form of lattice structure, and it can be considered an important algebraic structure in the set-valued information system. Meanwhile, the paper also offers some simple solutions to common problems, such as reduction, core. In short, this paper not only helps to explore the application range of concept lattice, but also offers a useful idea for the analysis and processing of set-valued information systems.
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备注/Memo
收稿日期:2016-3-28;改回日期:。
基金项目:国家自然科学基金项目(61273304,61202170);国家博士后科学基金项目(2014M560352);高等学校博士学科点专项科研基金项目(20130072130004).
作者简介:康向平,男,1982年生,博士后,主要研究方向为概念格、粗糙集、粒计算。苗夺谦,男,1964年生,教授,博士生导师,中国人工智能学会理事、中国计算机学会杰出会员、中国自动化学会智能自动化专委会委员、上海市计算机学会理事、上海市人工智能学会理事,主要研究方向为粗糙集、粒计算、Web智能、数据挖掘和机器学习。主持完成国家级、省部级自然科学基金与科技攻关项目多项,参与完成973计划项目、863计划项目、国家自然科学基金重大研究计划项目、上海市科委重大科技攻关项目等多项。作为项目组成员,曾获国家教委科技进步三等奖、教育部科技进步一等奖、上海市技术发明一等奖、重庆市自然科学一等奖等。发表学术论文260余篇,其中被SCI或EI检索150余篇.编著教材及著作12部,获得专利授权9项。
通讯作者:康向平.E-mail:tongji_kangxp@sina.com.
更新日期/Last Update:
1900-01-01