Sink Node Elimination to Enhance the Performance of Overlapping Detection Algorithms along with Comparison of Existing Algorithm
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          | Published in | Indian journal of science and technology Vol. 10; no. 19; pp. 1 - 5 | 
|---|---|
| Main Authors | , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
          
        01.02.2017
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| Online Access | Get full text | 
| ISSN | 0974-6846 0974-5645 0974-5645  | 
| DOI | 10.17485/ijst/2017/v10i19/113208 | 
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| Author | Kumar, Er. Rohit Arora, Er. Harpreet  | 
    
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| References | Wang W, Zhang Y. (ref6) 2007; 158 Hung WL, Yang MS, Chen DH. (ref2) 2006; 27 Wang X, Wang Y, Wang L. (ref7) 2004; 25 Zhu W, Jiang J, Song C, Bao L. (ref10) 2012; 29 Ghosh S, Dubey S. (ref1) 2013 Ji Z, Xia Y, Sun Q, Cao G. (ref4) 2014; 253 Mingoti SA, Lima JO. (ref5) 2006; 174 Jierui X, Stephen K, Boleslaw KS. (ref11) 2013; 45 Wu KL. (ref8) 2012; 45 Chatzis SP. (ref3) 2011; 38 Wu KL,Yang MS. (ref9) 2002; 35  | 
    
| References_xml | – volume: 158 start-page: 2095 issue: (19) year: 2007 ident: ref6 article-title: On fuzzy clump validity indices. publication-title: Fuzzy Sets Syst. doi: https://doi.org/10.1016/j.fss.2007.03.004 – volume: 25 start-page: 1123 issue: (10) year: 2004 ident: ref7 article-title: Improving fuzzy c-means clustering based on feature-weight learning. publication-title: Pattern Recognit Lett. doi: 10.1016/j.patrec.2004.03.008 – volume: 45 start-page: 407 issue: (1) year: 2012 ident: ref8 article-title: Analysis of parameter selections for fuzzy c-means. publication-title: Pattern Recognitt. doi: https://doi.org/10.1016/j.patcog.2011.07.012 – volume: 27 start-page: 424 issue: (5) year: 2006 ident: ref2 article-title: Parameter selection for suppressed fuzzy c-means with an application to MRI segmentation. publication-title: Pattern Recognit Lett. doi: https://doi.org/10.1016/j.patrec.2005.09.005 – volume: 174 start-page: 1742 year: 2006 ident: ref5 article-title: Comparing SOM neural network with Fuzzy C-means, K-means and traditional hierarchical clumping algorithms. publication-title: Eur J Oper Res. doi: https://doi.org/10.1016/j.ejor.2005.03.039 – volume: 253 start-page: 138 year: 2014 ident: ref4 article-title: Interval-valued possibilistic fuzzy C-means clumping algorithm. publication-title: Fuzzy Sets Syst. doi: https://doi.org/10.1016/j.fss.2013.12.011 – volume: 35 start-page: 2267 issue: (10) year: 2002 ident: ref9 article-title: Alternative c-means clustering algorithms. publication-title: Pattern Recognitt. doi: https://doi.org/10.1016/S0031-3203%2801%2900197-2 – start-page: 35 year: 2013 ident: ref1 article-title: Comparative analysis of K-means and Fuzzy C-Means Algorithms. publication-title: IJACSA – volume: 29 start-page: 3307 year: 2012 ident: ref10 article-title: Clustering algorithm based on Fuzzy C-means and Artificial Fish Swarm. publication-title: Procedia Eng. doi: https://doi.org/10.1016/j.proeng.2012.01.485 – volume: 38 start-page: 8684 issue: (7) year: 2011 ident: ref3 article-title: A fuzzy c-means-type algorithms for clumping of data with mixed numeric and categorical attributes employing a probabilistic dissimilarity functional. publication-title: Expert Syst Appl. doi: https://doi.org/10.1016/j.eswa.2011.01.074 – volume: 45 start-page: 43 issue: (4) year: 2013 ident: ref11 article-title: Overlapping Group Detection in Networks: The State-of-the-Art and Comparative Study. publication-title: ACM Computing Surveys.  | 
    
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| Title | Sink Node Elimination to Enhance the Performance of Overlapping Detection Algorithms along with Comparison of Existing Algorithm | 
    
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