An analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners
Document clustering has been investigated for use in a number of different areas of information retrieval. This study applies hierarchical based document clustering and neural network based document clustering to suggest supervisors and examiners for thesis. The results of both techniques were compa...
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| 格式: | Thesis |
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2005
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| 在线阅读: | http://eprints.utm.my/id/eprint/3600/1/NurulNisaMohdMFSKSM2005.pdf |
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my-utm-ep.36002018-01-07T08:19:32Z An analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners 2005-11 Mohd. Nasir, Nurul Nisa QA76 Computer software Document clustering has been investigated for use in a number of different areas of information retrieval. This study applies hierarchical based document clustering and neural network based document clustering to suggest supervisors and examiners for thesis. The results of both techniques were compared to the expert survey. The collection of 206 theses was used and employed the pre-processed using stopword removal and stemming. Inter document similarity were measured using Euclidean distance before clustering techniques were applied. The results show that Ward’s algorithm is better for suggestion supervisor and examiner compared to Kohonen network. 2005-11 Thesis http://eprints.utm.my/id/eprint/3600/ http://eprints.utm.my/id/eprint/3600/1/NurulNisaMohdMFSKSM2005.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System |
| institution |
Universiti Teknologi Malaysia |
| collection |
UTM Institutional Repository |
| language |
English |
| topic |
QA76 Computer software |
| spellingShingle |
QA76 Computer software Mohd. Nasir, Nurul Nisa An analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners |
| description |
Document clustering has been investigated for use in a number of different areas of information retrieval. This study applies hierarchical based document clustering and neural network based document clustering to suggest supervisors and examiners for thesis. The results of both techniques were compared to the expert survey. The collection of 206 theses was used and employed the pre-processed using stopword removal and stemming. Inter document similarity were measured using Euclidean distance before clustering techniques were applied. The results show that Ward’s algorithm is better for suggestion supervisor and examiner compared to Kohonen network. |
| format |
Thesis |
| qualification_level |
Master's degree |
| author |
Mohd. Nasir, Nurul Nisa |
| author_facet |
Mohd. Nasir, Nurul Nisa |
| author_sort |
Mohd. Nasir, Nurul Nisa |
| title |
An analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners |
| title_short |
An analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners |
| title_full |
An analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners |
| title_fullStr |
An analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners |
| title_full_unstemmed |
An analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners |
| title_sort |
analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners |
| granting_institution |
Universiti Teknologi Malaysia, Faculty of Computer Science and Information System |
| granting_department |
Faculty of Computer Science and Information System |
| publishDate |
2005 |
| url |
http://eprints.utm.my/id/eprint/3600/1/NurulNisaMohdMFSKSM2005.pdf |
| _version_ |
1747814459511930880 |