Multi-Criteria Mapping Based on Support Vector Machine and Cluster Distance

There was an increase in a number of applications for a master degree program with the growth in time. It takes huge time to process all the application documents of each and every applicant manually and requires a high volume of the workforce. This can be reduced if automation is used for this proc...

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Bibliographic Details
Main Author: Eerla, Vishwa Shanthi
Other Authors: TU Chemnitz, Fakultät für Informatik
Format: Dissertation
Language:English
Published: Universitätsbibliothek Chemnitz 2016
Subjects:
Online Access:http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-212565
http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-212565
http://www.qucosa.de/fileadmin/data/qucosa/documents/21256/Master_Thesis_Vishwa_Shanthi_Eerla.pdf
http://www.qucosa.de/fileadmin/data/qucosa/documents/21256/signatur.txt.asc
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spelling ndltd-DRESDEN-oai-qucosa.de-bsz-ch1-qucosa-2125652016-11-02T03:30:12Z Multi-Criteria Mapping Based on Support Vector Machine and Cluster Distance Eerla, Vishwa Shanthi Informatik Support Vektor Maschine Cluster Computer Science Support Vector Machine Cluster ddc:000 Informatik Cluster Anwendung Automation There was an increase in a number of applications for a master degree program with the growth in time. It takes huge time to process all the application documents of each and every applicant manually and requires a high volume of the workforce. This can be reduced if automation is used for this process. In any case, before that, an analysis of the complete strides required in preparing was precisely the automation must be utilized to diminish the time and workforces must be finished. The application process for the applicant is actually participating in several steps. First, the applicant sends the complete scanned documents to the uni-assist; from there the applications are received by the student assistant team at the particular university to which the applicant had applied, and then they are sent to the individual departments. At the individual sections, the individual applications will be handled by leading an intensive study to know whether the applicant by their past capabilities scopes to satisfy the prerequisites of further study system to which they have applied. What's more, by considering the required points of interest of the applicant without investigating every single report, and to pack the information and diminish the preparing time for the specific division, by this postulation extend a solitary web apparatus is being produced that can procedure the application which is much dependable in the basic leadership procedure of application. Universitätsbibliothek Chemnitz TU Chemnitz, Fakultät für Informatik Prof. Dr. Wolfram Hardt Daniel Reißner Prof. Dr. Wolfram Hardt Daniel Reißner 2016-11-01 doc-type:masterThesis application/pdf text/plain application/zip http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-212565 urn:nbn:de:bsz:ch1-qucosa-212565 http://www.qucosa.de/fileadmin/data/qucosa/documents/21256/Master_Thesis_Vishwa_Shanthi_Eerla.pdf http://www.qucosa.de/fileadmin/data/qucosa/documents/21256/signatur.txt.asc eng
collection NDLTD
language English
format Dissertation
sources NDLTD
topic Informatik
Support Vektor Maschine
Cluster
Computer Science
Support Vector Machine
Cluster
ddc:000
Informatik
Cluster
Anwendung
Automation
spellingShingle Informatik
Support Vektor Maschine
Cluster
Computer Science
Support Vector Machine
Cluster
ddc:000
Informatik
Cluster
Anwendung
Automation
Eerla, Vishwa Shanthi
Multi-Criteria Mapping Based on Support Vector Machine and Cluster Distance
description There was an increase in a number of applications for a master degree program with the growth in time. It takes huge time to process all the application documents of each and every applicant manually and requires a high volume of the workforce. This can be reduced if automation is used for this process. In any case, before that, an analysis of the complete strides required in preparing was precisely the automation must be utilized to diminish the time and workforces must be finished. The application process for the applicant is actually participating in several steps. First, the applicant sends the complete scanned documents to the uni-assist; from there the applications are received by the student assistant team at the particular university to which the applicant had applied, and then they are sent to the individual departments. At the individual sections, the individual applications will be handled by leading an intensive study to know whether the applicant by their past capabilities scopes to satisfy the prerequisites of further study system to which they have applied. What's more, by considering the required points of interest of the applicant without investigating every single report, and to pack the information and diminish the preparing time for the specific division, by this postulation extend a solitary web apparatus is being produced that can procedure the application which is much dependable in the basic leadership procedure of application.
author2 TU Chemnitz, Fakultät für Informatik
author_facet TU Chemnitz, Fakultät für Informatik
Eerla, Vishwa Shanthi
author Eerla, Vishwa Shanthi
author_sort Eerla, Vishwa Shanthi
title Multi-Criteria Mapping Based on Support Vector Machine and Cluster Distance
title_short Multi-Criteria Mapping Based on Support Vector Machine and Cluster Distance
title_full Multi-Criteria Mapping Based on Support Vector Machine and Cluster Distance
title_fullStr Multi-Criteria Mapping Based on Support Vector Machine and Cluster Distance
title_full_unstemmed Multi-Criteria Mapping Based on Support Vector Machine and Cluster Distance
title_sort multi-criteria mapping based on support vector machine and cluster distance
publisher Universitätsbibliothek Chemnitz
publishDate 2016
url http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-212565
http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-212565
http://www.qucosa.de/fileadmin/data/qucosa/documents/21256/Master_Thesis_Vishwa_Shanthi_Eerla.pdf
http://www.qucosa.de/fileadmin/data/qucosa/documents/21256/signatur.txt.asc
work_keys_str_mv AT eerlavishwashanthi multicriteriamappingbasedonsupportvectormachineandclusterdistance
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