属性探索算法的一种改进方法
An Improving Method on Attribute Exploration Algorithms
摘要
在介绍了形式概念分析中的伪内涵和属性探索算法之后,通过对属性探索算法进行研究,该算法的一种新改进方法被给出了。
The article introduces pseudo-intent and attribute exploration algorithms in formal concept analysis, By researching into the attribute'exploration algorithms, the article also gives an improving method on this algorithms.
关键词
形式概念分析
伪内涵
属性探索算法
改进算法
Formal Concept Analysis
Pseudo-intent
Attribute Exploration Algorithms
Improving Method
二级参考文献18
-
1Oosthuizen G D. The Application of Concept Lattice to Machine Learning. Technical Report, University of Pretoria, South Africa, 1996. 被引量:1
-
2Ho T B. Incremental conceptual clustering in the framework of Galois lattice. In: Lu H, Motoda H, Liu H, eds. KDD: Techniques and Applications. Singapore: World Scientific, 1997. 49~64. 被引量:1
-
3Kent R E. Bowman C M. Digital Libraries, Conceptual Knowledge Systems and the Nebula Interface. Technical Report, University of Arkansas, 1995. 被引量:1
-
4Corbett D, Burrow A L. Knowledge reuse in SEED exploiting conceptual graphs. In: International Conference on Conceptual Graphs (ICCS'96). Sydney, 1996. University of New South Wales, 1996. 56~60. 被引量:1
-
5Schmitt I, Saake G. Merging Inheritance hierarchies for scheme integration based on concept lattices [EB/OL]. http: //www.mathematic.tu-darm stadt.de/ags/ag1. 被引量:1
-
6Siff M, Reps T. Identifying modules via concept analysis. In: Harrold M J, Visaggio G, eds. International conference on software maintenance. Bari, Italy. Washington, DC: IEEE Computer Society, 1997. 170~179. 被引量:1
-
7Ho T B. An approach to concept formation based on formal concept analysis. IEICE Trans Information and Systems, 1995, E782D (5): 553~559. 被引量:1
-
8Carpineto C, Romano G. Galois: an order-theoretic approach to conceptual clustering. In: Utgoff P, ed. Proceedings of ICML 293. Amherst: Elsevier, 1993. 33~40. 被引量:1
-
9Godin R. Incremental concept formation algorithm based on Galois (concept) lattices. Computational Intelligence, 1995, 11(2): 246~267. 被引量:1
-
10Yao Y Y. Concept lattices in rough set theory. In: Dick S, Kurgan L, Pedrycz W, eds. Proceedings of 2004 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS 2004), IEEE Catalog Number: 04TH8736, 2004, June 27~30. 796~801. 被引量:1
共引文献193
-
1马捷,葛岩,蒲泓宇.属性约简方法研究综述[J].数据分析与知识发现,2020,4(1):40-50. 被引量:10
-
2范敏,任文秀,李金海.网络形式背景下的知识流动方法研究[J].模糊系统与数学,2023,37(1):58-74.
-
3降惠.概念格理论研究进展与发展综述[J].办公自动化,2019,24(9):18-21.
-
4吕跃进,李金海.基于一一映射的概念格属性约简算法[J].计算机应用研究,2009,26(3):849-851. 被引量:4
-
5李立峰,王国俊.一种求概念格属性约简的方法[J].计算机工程与应用,2006,42(20):147-149. 被引量:13
-
6马骏,沈夏炯.基于n阶形式背景核的概念格重构[J].河南大学学报(自然科学版),2007,37(1):71-74.
-
7仇国芳,陈劲.概念格的规则约简与属性特征[J].浙江大学学报(理学版),2007,34(2):158-162. 被引量:7
-
8安广伟,沈夏炯,张磊,贾培艳,张柯.n阶形式背景核的构造算法[J].计算机工程与设计,2007,28(7):1501-1503.
-
9刘利峰,吴孟达,王丹.基于属性约简的概念格构造[J].计算机工程与科学,2007,29(6):140-142. 被引量:5
-
10梁吉业,钱宇华.信息系统中熵度量的粒化单调性[J].山西大学学报(自然科学版),2007,30(2):156-162. 被引量:1
-
1张维,赵小香,曹发生,余泉.属性探索算法在知识发现中的应用研究[J].毕节学院学报(综合版),2010,28(4):1-8.
-
2赵小香,覃萍,王驹.属性探索算法研究[J].计算机科学与探索,2009,3(5):509-518. 被引量:3
-
3唐素勤,蔡自兴,王驹,蒋运承.运用属性探索构建完备描述逻辑本体[J].模式识别与人工智能,2011,24(1):1-13. 被引量:2