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山东大学学报（理学版） ›› 2015, Vol. 50 ›› Issue (12): 58-64.doi: 10.6040/j.issn.1671-9352.1.2015.051

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基于概念格的知识发现及其在高校就业数据分析中的应用

覃丽珍1, 李金海2, 王扬扬2   

  1. 1. 昆明理工大学城市学院, 云南 昆明 650051;
    2. 昆明理工大学理学院, 云南 昆明 650500
  • 收稿日期:2015-04-25 修回日期:2015-09-09 出版日期:2015-12-20 发布日期:2015-12-23
  • 通讯作者: 李金海(1984-),男,博士,副教授,研究方向为粗糙集、概念格与粒计算.E-mail:jhlixjtu@163.com E-mail:jhlixjtu@163.com
  • 作者简介:覃丽珍(1982-),女,硕士,助教,研究方向为粗糙集与概念格.E-mail:33942864@qq.com
  • 基金资助:
    国家自然科学基金资助项目(61305057);昆明理工大学“提高经济困难学生综合能力”资助项目(201420)

Concept lattice based knowledge discovery and its application to analysis of employment data in universities

QIN Li-zhen1, LI Jin-hai2, WANG Yang-yang2   

  1. 1. City College, Kunming University of Science and Technology, Kunming 650051, Yunnan, China;
    2. Faculty of Science, Kunming University of Science and Technology, Kunming 650500, Yunnan, China
  • Received:2015-04-25 Revised:2015-09-09 Online:2015-12-20 Published:2015-12-23

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摘要： 形式概念分析是数据分析与知识发现的有效工具,现已被广泛应用于各个研究领域。决策形式背景是形式概念分析中的重要关系数据库之一,其主要研究内容是基于规则提取的知识发现。本文借助于Wille概念格和面向对象概念格对决策形式背景的规则提取问题进行研究,给出了规则提取算法,并通过高校就业数据对算法进行了实证分析。

关键词: 知识发现, 决策形式背景, 就业数据分析, 概念格, 规则提取

Abstract: Formal concept analysis is an effective tool in data analysis and knowledge discovery, and it has been applied in various fields. Formal decision context is one of the key relational datasets in formal concept analysis and rule acquisition based knowledge discovery is its main research topic. In this paper, Wille's concept lattice and object-oriented concept lattice are used to study rule acquisition in formal decision context, the corresponding rule acquisition algorithm is explored, and employment data from universities is employed to illustrate the feasibility of the proposed algorithm.

Key words: formal decision context, knowledge discovery, concept lattice, rule acquisition, analysis of employment data

中图分类号: 

  • TP301
[1] WILLE R. Restructuring lattice theory: an approach based on hierarchies of concepts[C]. Ordered Sets, 1982: 445-470.
[2] 张文修,仇国芳. 基于粗糙集的不确定性决策[M]. 北京:清华大学出版社,2005. ZHANG Wenxiu, QIU Guofang. Uncertain decision making based on rough sets[M]. Beijing: Tsinghua University Press, 2005.
[3] 王志海,胡可云,胡学刚,等. 概念格上规则提取的一般算法与渐进式算法[J].计算机学报, 1999, 22(1):66-70. WANG Zhihai, HU Keyun, HU Xuegang, et al. General and incremental algorithms of rule extraction based on concept lattice[J]. Chinese Journal of Computers, 1999, 22(1):66-70.
[4] 谢志鹏,刘宗田. 概念格的快速渐进式构造算法[J].计算机学报, 2002, 25(5):490-495. XIE Zhipeng, LIU Zongtian. A fast incremental algorithm for building concept lattice[J]. Chinese Journal of Computers, 2002, 25(5):490-495.
[5] 梁吉业,王俊红.基于概念格的规则产生集挖掘算法[J].计算机研究与发展, 2004, 41(8):1339-1344. LIANG Jiye, WANG Junhong. An algorithm for extracting rule-generating sets based on concept lattice[J]. Journal of Computers Research & Development, 2004, 41(8):1339-1344.
[6] 张文修,魏玲,祁建军. 概念格的属性约简理论与方法[J]. 中国科学:F辑 信息科学, 2005, 35(6):628-639. ZHANG Wenxiu, WEI Ling, QI Jianjun. Attribute reduction theory and approach to concept lattice[J]. Science in China: Series F Information Sciences, 2005, 35(6):628-639.
[7] 张继福,蒋义勇,胡立华,等. 基于概念格的天体光谱离群数据识别方法[J]. 自动化学报, 2008, 34(9):1060-1066. ZHANG Jifu, JIANG Yiyong, HU Lihua, et al. A concept lattice based recognition method of celestial spectra outliers[J]. Acta Automatica Sinica, 2008, 34(9):1060-1066.
[8] 智慧来,智东杰,刘宗田.概念格合并原理与算法[J].电子学报, 2010, 38(2):455-459. ZHI Huilai, ZHI Dongjie, LIU Zongtian. Theory and algorithm of concept lattice union[J]. Chinese Journal of Electronics, 2010, 38(2):455-459.
[9] WU Weizhi, LEUNG Yee, MI Jusheng. Granular computing and knowledge reduction in formal contexts[J]. IEEE Transactions on Knowledge and Data Engineering, 2009, 21(10):1461-1474.
[10] LI Jinhai, MEI Changlin, XU Weihua, et al. Concept learning via granular computing: A cognitive viewpoint[J]. Information Sciences, 2015, 298:447-467.
[11] 魏玲,祁建军,张文修. 决策形式背景的概念格属性约简[J]. 中国科学: F辑 信息科学,2008,38(2):195-208. WEI Ling, QI Jianjun, ZHANG Wenxiu. Attribute reduction theory of concept lattice based on decision formal contexts[J]. Science in China: Series F Information Sciences, 2008, 38(2):195-208.
[12] SHAO Mingwen, LEUNG Yee, WU Weizhi. Rule acquisition and complexity reduction in formal decision contexts[J]. International Journal of Approximate Reasoning, 2014, 55(1):259-274.
[13] LI Jinhai, MEI Changlin, LV Yuejin. Knowledge reduction in formal decision contexts based on an order-preserving mapping[J]. International Journal of General Systems, 2012, 41(2):143-161.
[14] LI Jinhai, MEI Changlin, LV Yuejin. Knowledge reduction in decision formal contexts[J]. Knowledge-Based Systems, 2011, 24(5):709-715.
[15] LI Jinhai, MEI Changlin, LV Yuejin. A heuristic knowledge-reduction method for decision formal contexts[J]. Computers and Mathematics with Applications, 2011, 61(4):1096-1106.
[16] LI Jinhai, MEI Changlin, CHERUKURI A K, et al. On rule acquisition in decision formal contexts[J]. International Journal of Machine Learning and Cybernetics, 2013, 4(6):721-731.
[17] LI Jinhai, MEI Changlin, WANG Junhong, et al. Rule-preserved object compression in formal decision contexts using concept lattices[J]. Knowledge-Based Systems, 2014, 71(11):435-445.
[18] REN Yue, LI Jinhai, CHERUKURI A K, et al. Rule acquisition in formal decision contexts based on formal, object-oriented and property-oriented concept lattices[J]. The Scientific World Journal, 2014(2014):1-10.
[19] 覃丽珍,姚炳学,李金海. 不协调覆盖决策系统的完备属性约简算法[J]. 模糊系统与数学,2013, 27(5):158-166. QIN Lizhen, YAO Bingxue, LI Jinhai. A complete attribute reduction algorithm for inconsistent covering decision systems[J]. Fuzzy Systems and Mathematics, 2013, 27(5):158-166.
[20] 麦晓冬,贾萍,翁建荣,等. 基于多尺度粗糙集模型的决策树在高校就业数据分析中的应用[J]. 华南师范大学学报:自然科学版,2014, 46(4):31-36. MAI Xiaodong, JIA Ping, WENG Jianrong, et al. Analysis of employment data in universities using multi-scale rough set model decision trees[J]. Journal of South China Normal University:Natural Science Edition, 2014, 46(4):31-36.
[21] YAO Yiyu. Concept lattices in rough set theory[C]// Proceedings of 23rd International Meeting of the North American Fuzzy Information Processing Society, IEEE Xplore, 2004: 796-801.
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