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10.1186/s13040-018-0172-x http://scihub22266oqcxt.onion/10.1186/s13040-018-0172-x C6047369!6047369!30026812     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       BioData+Min 2018 ; 11 (ä): ä Nephropedia Template TP {{tp|p=30026812|t=2018. Soft document clustering using a novel graph covering approach |pdf=|usr=}}{{30026812}} gab.com Text Soft document clustering using a novel graph covering approach JO: BioData Min http://www.kidney.de/pget.php?&tw=1&pmid=30026812 #FOAvip Background: In text mining, document clustering describes the efforts to assign unstructured documents to clusters, which in turn usually refer to topics. Clustering is widely used in science for data retrieval and organisation. Results: In this paper we present and discuss a novel graph-theoretical approach for document clustering and its application on a real-world data set. We will show that the well-known graph partition to stable sets or cliques can be generalized to pseudostable sets or pseudocliques. This allows to perform a soft clustering as well as a hard clustering. The software is freely available on GitHub. Conclusions: The presented integer linear programming as well as the greedy approach for this \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\mathcal {NP}$\end{document}NP-complete problem lead to valuable results on random instances and some real-world data for different similarity measures. We could show that PS-Document Clustering is a remarkable approach to document clustering and opens the complete toolbox of graph theory to this field. Electronic supplementary material: The online version of this article (10.1186/s13040-018-0172-x) contains supplementary material, which is available to authorized users. Twit Text FOAVip Soft document clustering using a novel graph covering approach ????BioData Min http://www.kidney.de/pget.php?&tw=1&pmid=30026812 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=30026812 #FOAvip English Wikipedia <ref>{{Cite pmid|30026812}}</ref> Soft document clustering using a novel graph covering approach #MMPMID30026812 Dörpinghaus J; Schaaf S; Jacobs M BioData Min 2018[]; 11 (ä): ä PMID30026812show ga Background: In text mining, document clustering describes the efforts to assign unstructured documents to clusters, which in turn usually refer to topics. Clustering is widely used in science for data retrieval and organisation. Results: In this paper we present and discuss a novel graph-theoretical approach for document clustering and its application on a real-world data set. We will show that the well-known graph partition to stable sets or cliques can be generalized to pseudostable sets or pseudocliques. This allows to perform a soft clustering as well as a hard clustering. The software is freely available on GitHub. Conclusions: The presented integer linear programming as well as the greedy approach for this \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\mathcal {NP}$\end{document}NP-complete problem lead to valuable results on random instances and some real-world data for different similarity measures. We could show that PS-Document Clustering is a remarkable approach to document clustering and opens the complete toolbox of graph theory to this field. Electronic supplementary material: The online version of this article (10.1186/s13040-018-0172-x) contains supplementary material, which is available to authorized users. äSoft document clustering using a novel graph covering approach (epmc).pdf DeepDyve Pubget Overpricing