Evaluating algorithms for an expertise recommender system
This study evaluates two algorithms, Support Vector Machine and Bayesian Logistic Regression as applied to an Expertise Recommender System, and compares the results. The expertise area examined is academic research, the information being extracted from faculty web pages of universities world-wide. T...
محفوظ في:
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| التنسيق: | Theses and Dissertations |
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2008
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10356/1907 |
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| المؤسسة: | Nanyang Technological University |
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sg-ntu-dr.10356-1907 |
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sg-ntu-dr.10356-19072019-12-10T14:46:29Z Evaluating algorithms for an expertise recommender system Uma Manikantan Goh, Dion Hoe Lian Wee Kim Wee School of Communication and Information DRNTU::Library and information science::Libraries::Technologies This study evaluates two algorithms, Support Vector Machine and Bayesian Logistic Regression as applied to an Expertise Recommender System, and compares the results. The expertise area examined is academic research, the information being extracted from faculty web pages of universities world-wide. The study is aimed at the ability of distinguishing subject specialisations within a main subject. Master of Science (Information Studies) 2008-09-10T08:37:16Z 2008-09-10T08:37:16Z 2004 2004 Thesis http://hdl.handle.net/10356/1907 Nanyang Technological University application/pdf |
| institution |
Nanyang Technological University |
| building |
NTU Library |
| country |
Singapore |
| collection |
DR-NTU |
| topic |
DRNTU::Library and information science::Libraries::Technologies |
| spellingShingle |
DRNTU::Library and information science::Libraries::Technologies Uma Manikantan Evaluating algorithms for an expertise recommender system |
| description |
This study evaluates two algorithms, Support Vector Machine and Bayesian Logistic Regression as applied to an Expertise Recommender System, and compares the results. The expertise area examined is academic research, the information being extracted from faculty web pages of universities world-wide. The study is aimed at the ability of distinguishing subject specialisations within a main subject. |
| author2 |
Goh, Dion Hoe Lian |
| author_facet |
Goh, Dion Hoe Lian Uma Manikantan |
| format |
Theses and Dissertations |
| author |
Uma Manikantan |
| author_sort |
Uma Manikantan |
| title |
Evaluating algorithms for an expertise recommender system |
| title_short |
Evaluating algorithms for an expertise recommender system |
| title_full |
Evaluating algorithms for an expertise recommender system |
| title_fullStr |
Evaluating algorithms for an expertise recommender system |
| title_full_unstemmed |
Evaluating algorithms for an expertise recommender system |
| title_sort |
evaluating algorithms for an expertise recommender system |
| publishDate |
2008 |
| url |
http://hdl.handle.net/10356/1907 |
| _version_ |
1681035336775368704 |