Journal of Shandong University(Engineering Science) ›› 2018, Vol. 48 ›› Issue (6): 74-81.doi: 10.6040/j.issn.1672-3961.0.2018.208

• Machine Learning & Data Mining • Previous Articles     Next Articles

Linguistic concept formal decision context analysis based on granular computing

Kuo PANG(),Siqi CHEN,Xiaoying SONG,Li ZOU*()   

  1. College of Computer and Information Technology, Liaoning Normal University, Dalian 116081, Liaoning, China
  • Received:2018-05-25 Online:2018-12-20 Published:2018-12-26
  • Contact: Li ZOU E-mail:pangkuolnnu@163.com;zoulicn@163.com
  • Supported by:
    国家自然科学基金项目(61772250);国家自然科学基金项目(61673320);国家自然科学基金项目(61672127);中央高校基本科研业务费项目(2682017ZT12);辽宁省自然科学基金项目(2015020059)

RichHTML

9

PDF (PC)

1166

Abstract:

Aiming at the decision problem with linguistic value information, combining linguistic terminology and information system, the linguistic decision information system and linguistic concept was proposed, and the related properties of linguistic concept were discussed. By transforming linguistic decision information systems, the linguistic concept formal decision context was proposed. In order to expand the intent and extent of the linguistic concept lattice, the scale of the linguistic concept was compressed, and the granular linguistic concept formal decision context was proposed by granulating the linguistic concept. The granular computing was introduced into the granular linguistic concept formal decision context, and a rule extraction model based on granular computing for linguistic concept formal decision context was constructed by using coverage and confidence. Medical diagnostic examples illustrated the effectiveness and utility of this method in obtaining high quality rules.

Key words: granular computing, linguistic concept formal decision context, rule extraction, granular rule

CLC Number: 

  • TP181

Table 1

Linguistic decision information system in diagnosis of gastrointestinal cold"

U a b c d e
x1 s1 s0 s2 t1 t-1
x2 s-2 s-2 s-2 t-2 t2
x3 s2 s2 s2 t2 t-2
x4 s0 s0 s1 t0 t0
x5 s1 s2 s2 t2 t-2
x6 s-2 s2 s0 t2 t-1

Table 2

Linguistic concept formal decision context in diagnosis of gastrointestinal cold"

U as-2 as-1 as0 as1 as2 bs-2 bs-1 bs0 bs1 bs2 cs-2 cs-1 cs0 cs1 cs2
x1 × × ×
x2 × × ×
x3 × × ×
x4 × × ×
x5 × × ×
x6 × × ×
U ds-2 ds-1 ds0 ds1 ds2 es-2 es-1 es0 es1 es2
x1 × ×
x2 × ×
x3 × ×
x4 × ×
x5 × ×
x6 × ×

Table 3

The granular linguistic concept formal decision context obtained from Table 2"

U [a]sλ1- [a]sλ1+ [b]sλ1- [b]sλ1+ [c]sλ1- [c]sλ1+ [d]tλ2- [d]tλ2+
x1 × × × ×
x2 × × × ×
x3 × × × ×
x4 × × × ×
x5 × × × ×
x6 × × × ×

Table 4

The granular linguistic concept formal decision context after reduction"

U [a]sλ1- [a]sλ1+ [b]sλ1- [b]sλ1+ [c]sλ1- [c]sλ1+ [d]tλ2- [d]tλ2+
x1 × × × ×
x2 × × × ×
x3 × × × ×
x4 × × × ×
x5 × × × ×
1 WILLE R . Restructuring lattice theory: an approach based on hierarchies of concepts[J]. Orderd Sets D Reidel, 1982, 83, 314- 339.
2 GANTRER B . Formal concept analysis: mathematical foundations[M]. New York, USA: Springer-Verlag New York, Inc., 1999.
3 KANG Xiangping , LI Deyu , WANG Suge , et al. Formal concept analysis based on fuzzy granularity base for different granulations[J]. Fuzzy Sets and Systems, 2012, 203 (21): 33- 48.
4 YAO Yiyu. A comparative study of formal concept analysis and rough set theory in data analysis[C]//International Conference on Rough Sets and Current Trends in Computing. Berlin Heidelberg, Germany: Springer, 2004: 59-68.
5 LI Jinhai , HUANG Chenchen , QI Jianjun . Three-way cognitive concept learning via multi-granularity[J]. Information Sciences, 2017, 378 (1): 244- 263.
6 QIAN T , WEI L , QI J . Constructing three-way concept lattices based on apposition and subposition of formal contexts[J]. Knowledge-Based Systems, 2017, 116, 39- 48.
doi: 10.1016/j.knosys.2016.10.033
7 QI J , QIAN T , WEI L . The connections between three-way and classical concept lattices[J]. Knowledge-Based Systems, 2016, 91 (C): 143- 151.
8 KONECNY J , KRIDLO O . On biconcepts in formal fuzzy concept analysis[J]. Information Sciences, 2017, 375, 16- 29.
doi: 10.1016/j.ins.2016.09.042
9 ALCALDE C , BURUSCO A . The use of two relations in L-fuzzy contexts[M]. Amsterdam, Netherlands: Elsevier Science Inc., 2015.
10 LI J , REN Y , MEI C , et al. A comparative study of multigranulation rough sets and concept lattices via rule acquisition[J]. Knowledge-Based Systems, 2016, 91, 152- 164.
doi: 10.1016/j.knosys.2015.07.024
11 ZHI H , LI J . Granule description based on formal concept analysis[J]. Knowledge-Based Systems, 2016, 104 (1): 62- 73.
12 KANG Xiangping , MIAO Duoqian . A study on information granularity in formal concept analysis based on concept-bases[M]. Amsterdam, Netherlands: Elsevier Science Publishers B. V., 2016.
13 YAO Y . Rough-set concept analysis: interpreting RS-definable concepts based on ideas from formal concept analysis[J]. Information Sciences, 2016, 346, 442- 462.
14 ZOU L , ZHANG Z , LONG J . An efficient algorithm for increasing the granularity levels of attributes in formal concept analysis[J]. Expert Systems with Applications, 2016, 46, 224- 235.
doi: 10.1016/j.eswa.2015.10.026
15 PEI Z , RUAN D . Formal concept analysis based on the topology for attributes of a formal context[J]. Information Sciences, 2013, 236, 66- 82.
doi: 10.1016/j.ins.2013.02.027
16 MEDINA J . Relating attribute reduction in formal, object-oriented and property-oriented concept lattices[J]. Computers & Mathematics with Applications, 2012, 64 (6): 1992- 2002.
17 DIAS S M , VIEIRA N J . Concept lattices reduction: dDefinition, analysis and classification[J]. Expert Systems with Applications, 2015, 42 (20): 7084- 7097.
doi: 10.1016/j.eswa.2015.04.044
18 李进金, 张燕兰, 吴伟志, 等. 形式背景与协调决策形式背景属性约简与概念格生成[J]. 计算机学报, 2014, 37 (8): 1768- 1774.
LI Jinjin , ZHANG Yanlan , WU Zhiwei , et al. Attribute reduction for formal context and consistent decision formal context and concept lattice generation[J]. Chinese Journal of Computers, 2014, 37 (8): 1768- 1774.
19 ZHUA W . The fourth type of covering-based rough sets[J]. Information Sciences, 2012, 201 (19): 80- 92.
20 张铃, 张钹. 模糊相容商空间与模糊子集[J]. 中国科学:信息科学, 2011, 41 (1): 1- 11.
ZHANG Ling , ZHANG Bo . Fuzzy compatible quotient spaces and fuzzy subsets[J]. Chinese Science: Information Science, 2011, 41 (1): 1- 11.
21 WU W Z , LEUNG Y , MI J S . Granular computing and knowledge reduction in formal contexts[J]. IEEE Transactions on Knowledge and Data Engineering, 2009, 21 (10): 1461- 1474.
doi: 10.1109/TKDE.2008.223
22 YAO Y . Interpreting concept learning in cognitive informatics and granular computing[J]. IEEE Press, 2009, 39 (4): 855- 866.
23 王国胤, 张清华, 马希骜, 等. 知识不确定性问题的粒计算模型[J]. 软件学报, 2011, 22 (4): 676- 694.
WANG Guoyin , ZHANG Qinghua , MA Xi'ao , et al. Granular computing models for knowledge uncertainty[J]. Journal of Software, 2011, 22 (4): 676- 694.
24 苗夺谦, 王国胤, 刘清, 等. 粒计算:过去、现在与展望[M]. 北京: 科学出版社, 2007.
25 徐久成, 孙林, 张倩倩. 粒计算及其不确定信息度量的理论与方法[M]. 北京: 科学出版社, 2013.
26 ZADEH L A . The Concept of a Linguistic Variable and its application to approximate reasoning[J]. Inf Sci, 1974, 8 (3): 199- 249.
27 WANG J H , HAO J . A new version of 2-tuple fuzzy linguistic representation model for computing with words[J]. IEEE Transactions on Fuzzy Systems, 2006, 14 (3): 435- 445.
doi: 10.1109/TFUZZ.2006.876337
28 HERRERA F , MARTINEZ L . A 2-tuple fuzzy linguistic representation model for computing with words[J]. IEEE Transactions on Fuzzy Systems, 2000, 8 (6): 746- 752.
doi: 10.1109/91.890332
29 LIAO H , XU Z , ZENG X J . Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making[J]. Information Sciences, 2014, 271 (3): 125- 142.
30 ZHAI Y . Study of decision implications based on formal concept analysis[J]. International Journal of General Systems, 2007, 36 (2): 147- 156.
doi: 10.1080/03081070600913650
[1] Yan PENG,Tingting FENG,Jie WANG. An integrated learning approach for O3 mass concentration prediction model [J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 1-7.
[2] Yibin WANG,Tianli LI,Yusheng CHENG,Kun QIAN. Label distribution learning based on kernel extreme learning machine auto-encoder [J]. Journal of Shandong University(Engineering Science), 2020, 50(3): 58-65.
[3] Chunyang LI,Nan LI,Tao FENG,Zhuhe WANG,Jingkai MA. Abnormal sound detection of washing machines based on deep learning [J]. Journal of Shandong University(Engineering Science), 2020, 50(2): 108-117.
[4] Yingda LI,Zongxia XIE. Support vector regression algorithm based on kernel similarity reduced strategy [J]. Journal of Shandong University(Engineering Science), 2019, 49(3): 8-14.
[5] WANG Tingting, ZHAI Junhai, ZHANG Mingyang, HAO Pu. K-NN algorithm for big data based on HBase and SimHash [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 54-59.
[6] HE Zhengyi, ZENG Xianhua, GUO Jiang. An ensemble method with convolutional neural network and deep belief network for gait recognition and simulation [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 88-95.
[7] CUI Xiaosong, WANG Ying, MENG Jia, ZOU Li. Online business self-evaluation system based on linguistic-valued similarity reasoning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(1): 1-7.
[8] YAO Yu, FENG Jian, ZHANG Huaguang, HAN Kezhen. Weighted hyper-ellipsoidal support vector data description with negative samples for outlier detection [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(5): 195-202.
[9] LI Sushu, WANG Shitong, LI Tao. A feature selection method based on LS-SVM and fuzzy supplementary criterion [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(3): 34-42.
[10] LIU Yingxia, WANG Xichang, TANG Xiaoli, CHANG Faliang. Object detection algorithm based on Bayesian probability estimation in wavelet domain [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(2): 63-70.
[11] HE Zhengyi, ZENG Xianhua, QU Shengwei, WU Zhilong. The time series prediction model based on integrated deep learning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 40-47.
[12] WANG Mei, ZENG Zhaohu, SUN Yingqi, YANG Erlong, SONG Kaoping. Bayesian combination of SVR on regularization path based on KNN of input [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 8-14.
[13] CHEN Zehua, SHANG Xiaohui, CHAI Jing. Neighborhood related multiple-instance classifiers based on integrated Hausdorff distance [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 15-22.
[14] WANG Zhiqiang, WEN Yimin, LI Fang. Collaborative recommendation for scenic spots based on multi-aspect ratings [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 54-61.
[15] HUANG Dan, WANG Zhihai, LIU Haiyang. A local collaborative filtering algorithm based on ranking recommendation tasks [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(5): 29-36.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] LI Kan . Empolder and implement of the embedded weld control system[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(4): 37 -41 .
[2] LAI Xiang . The global domain of attraction for a kind of MKdV equations[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 87 -92 .
[3] YU Jia yuan1, TIAN Jin ting1, ZHU Qiang zhong2. Computational intelligence and its application in psychology[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 1 -5 .
[4] CHEN Rui, LI Hongwei, TIAN Jing. The relationship between the number of magnetic poles and the bearing capacity of radial magnetic bearing[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(2): 81 -85 .
[5] WANG Bo,WANG Ning-sheng . Automatic generation and combinatory optimization of disassembly sequence for mechanical-electric assembly[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 52 -57 .
[6] ZHANG Ying,LANG Yongmei,ZHAO Yuxiao,ZHANG Jianda,QIAO Peng,LI Shanping . Research on technique of aerobic granular sludge cultivationby seeding EGSB anaerobic granular sludge[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(4): 56 -59 .
[7] Yue Khing Toh1， XIAO Wendong2， XIE Lihua1. Wireless sensor network for distributed target tracking: practices via real test bed development[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 50 -56 .
[8] SUN Weiwei， WANG Yuzhen. Finite gain stabilization of singlemachine infinite bus system subject to saturation[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 69 -76 .
[9] SUN Yu-li,LI De-fa,ZUO Dun-wen,QI mei . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(6): 19 -23 .
[10] WANG Yong, XIE Yudong. Gas control technology of largeflow pipe[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(2): 70 -74 .
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd