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why6116木虫 (小有名气)
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[求助]
帮忙看看下面几篇论文是否被EI收录或者ISTP收录，不甚感激~~~
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麻烦各位，帮忙看看下面几篇论文是否被EI收录或者ISTP收录，收录编号是多少？万分感谢 （1）论文：Context quantization based on the modified K-means clustering 作者：Min Chen, Fuyan Wang 发表于：Advanced Materials Research Vols. 756-759 (2013) doi:10.4028/www.scientific.net/AMR.756-759.4068 [ Last edited by lazy锦溪 on 2016-5-17 at 09:07 ] |
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why6116: 金币+30, ★★★★★最佳答案 2016-05-17 12:45:53
lazy锦溪: LS-EPI+1, 感谢应助！ 2016-05-17 13:00:38
感谢参与，应助指数 +1
why6116: 金币+30, ★★★★★最佳答案 2016-05-17 12:45:53
lazy锦溪: LS-EPI+1, 感谢应助！ 2016-05-17 13:00:38
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一贴一篇 第一篇的 Accession number: 20134416937557 Title: Context quantization based on the modified K-means clustering Authors: Chen, Min1 Email author minkeychen@sina.cn; Wang, Fu Yan2 Email author 757441312@qq.com Author affiliation: 1 College of Information Science, Yunnan University, Kunming, 650091, China 2 College of Information and Technology, Kunming University, Kunming, 650214, China Source title: Advanced Materials Research Abbreviated source title: Adv. Mater. Res. Volume: 756-759 Monograph title: Information Technology Applications in Industry, Computer Engineering and Materials Science Issue date: 2013 Publication year: 2013 Pages: 4068-4072 Language: English ISSN: 10226680 ISBN-13: 9783037857700 Document type: Conference article (CA) Conference name: 3rd International Conference on Materials Science and Information Technology, MSIT 2013 Conference date: September 14, 2013 - September 15, 2013 Conference location: Nanjing, Jiangsu, China Conference code: 100389 Sponsor: Trans tech publications inc.; Computer Science and Electronic Technology; BITS Narsampet; Universitatea Politehnica Din Bucuresti Publisher: Trans Tech Publications Ltd, Kreuzstrasse 10, Zurich-Durnten, CH-8635, Switzerland Abstract: The context quantization for I-ary source based on the modified K-means clustering algorithm is present in this paper. In this algorithm, the adaptive complementary relative entropy between two conditional probability distributions, which is used as the distance measure for K-means instead, is formulated to describe the similarity of these two probability distributions. The rules of the initialized centers chosen for K-means are also discussed. The proposed algorithm will traverse all possible number of the classes to search the optimal one which is corresponding to the shortest adaptive code length. Then the optimal context quantizer is achieved rapidly and the adaptive code length is minimized at the same time. Simulations indicate that the proposed algorithm produces better coding result than the result of other algorithm. © (2013) Trans Tech Publications, Switzerland. Number of references: 8 Main heading: Information technology Controlled terms: Clustering algorithms - Materials science - Optimal systems - Optimization - Probability distributions Uncontrolled terms: Adaptive code lengths - Conditional probability distributions - Context quantization - Distance measure - K-means - Model contexts - Modified k-means clustering - Relative entropy Classification code: 721 Computer Circuits and Logic Elements - 903 Information Science - 921.5 Optimization Techniques - 922.1 Probability Theory - 951 Materials Science DOI: 10.4028/www.scientific.net/AMR.756-759.4068 Database: Compendex Compilation and indexing terms, © 2016 Elsevier Inc. |
2楼2016-05-17 08:47:29