附件
EI 收录:
1. Accession number: 20101212793436
Title: A property optimization method in support of approximately duplicated records detecting
Authors: Mansheng, Xiao1 ; Youshi, Liu2 ; Xiaoqi, Zhou2
Author affiliation: 1 School of Science, Hunan University of Technology, Zhuzhou, 412008 Hunan,
China
2 College of Science and Technology, Hunan University of Technology, Zhuzhou, 412008 Hunan, China
Corresponding author: Mansheng, X. (xiaomansheng@tom.com)
Source title: Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent
Systems, ICIS 2009
Abbreviated source title: Proc. - IEEE Int. Conf. Intelligent Comput. Intelligent Syst., ICIS
Volume: 3
Monograph title: Proceedings - 2009 IEEE International Conference on Intelligent Computing and
Intelligent Systems, ICIS 2009
Issue date: 2009
Publication year: 2009
Pages: 118-122
Article number: 5358212
Language: English
ISBN-13: 9781424447541
Document type: Conference article (CA)
Conference name: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems,
ICIS 2009
Conference date: November 20, 2009 - November 22, 2009
Conference location: Shanghai, China
Conference code: 79567
Sponsor: IEEE Beijing Section; Shanghai Jiaotong University; Xiamen University; City University of
Hong Kong; Iwate Prefectural University
Publisher: IEEE Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United
States
Abstract: In approximately duplicated records detecting of large dataset, the composition of data is
complicated and the properties of data are too many, so the measurement accuracy is not high, the
implementation cost is oversized. In view of these problems, a sub-fuzzy clustering property optimization
method based on grouping is proposed. That is, first, the properties of group record are processed to reduce
the dimension of property effectively and obtain the representation of the group, and then a similarity
comparison method is used to detect approximately duplicated records in groups. It is shown in theoretical
analysis and experiment, this method has higher detection accuracy and efficiency, and could better solve the
recognition problems of approximately duplicated records in large dataset. ©2009 IEEE.
Number of references: 8
Main heading: Intelligent computing
Controlled terms: Cluster analysis - Fuzzy clustering - Fuzzy systems - Intelligent systems Optimization
Uncontrolled terms: Approximately Duplicated Records - Comparison methods - Data sets Detection accuracy - Implementation cost - Measurement accuracy - Optimization method Property Optimization
中国科技信息研究所
-1-
附件
EI 收录:
Classification code: 961 Systems Science - 922 Statistical Methods - 921.5 Optimization
Techniques - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory - 731.1 Control
Systems - 723.4 Artificial Intelligence - 723 Computer Software, Data Handling and Applications
DOI: 10.1109/ICICISYS.2009.5358212
Database: Compendex
Compilation and indexing terms, © 2009 Elsevier Inc.
2. Accession number: 20095312598094
Title: Research on image reconstruction technology by FCM of weighted characteristic
Authors: Xiao, Man-Sheng1 ; Lv, Yong1 ; Zeng, Rong1
Author affiliation: 1 College of Science, Hu'nan University of Technology, Zhuzhou 412008, China
Corresponding author: Xiao, M.-S. (xiaomansheng@tom.com)
Source title: Kongzhi yu Juece/Control and Decision
Abbreviated source title: Kongzhi yu Juece Control Decis
Volume: 24
Issue: 12
Issue date: December 2009
Publication year: 2009
Pages: 1917-1920
Language: Chinese
ISSN: 10010920
CODEN: KYJUEF
Document type: Journal article (JA)
Publisher: Northeast University, P.O. Box 125, Shenyang, 110005, China
Abstract: Aiming at a defect on randomness of the initial clustering center choosing and sensitivity of
initial value in tradition FCM(fuzzy C-means) algorithm, a clustering algorithm about FCM of weighted
color space based on evolutionary strategy is proposed. By interposing weighted matrix in RGB(Red Green
Blue) color space, the color's inhomogeneous is compensated. And by using a statistics clustering algorithm
of minimal maximal distance, clustering center is initiated. The experimental results show that the algorithm
can decrease effectively the mean square deviation of color quantization, keep overall arrangement of ideas
and part characteristic detail in image reconstruction, and has practical value to the study of the image
process technology.
Number of references: 10
Main heading: Clustering algorithms
Controlled terms: Color - Color image processing - Evolutionary algorithms - Fuzzy rules Fuzzy systems - Image reconstruction
Uncontrolled terms: Clustering centers - Color quantization - Color space - Evolutionary
strategies - Fuzzy C mean - Image process - Initial values - matrix - Mean square
deviation - Red green blues
Classification code: 961 Systems Science - 921.4 Combinatorial Mathematics, Includes Graph Theory,
Set Theory - 921 Mathematics - 903.1 Information Sources and Analysis - 741.1 Light/Optics 741 Light, Optics and Optical Devices - 731.1 Control Systems - 723.4 Artificial Intelligence 723.2 Data Processing and Image Processing - 723 Computer Software, Data Handling and Applications
中国科技信息研究所
-2-
附件
EI 收录:
- 721 Computer Circuits and Logic Elements
Database: Compendex
Compilation and indexing terms, © 2009 Elsevier Inc.
© 2009 Elsevier Inc. All rights reserved.
中国科技信息研究所
-3-