A comparison of taxonomy generation techniques using bibliometric methods : applied to research strategy formulation
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2011
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| Online Access: | http://hdl.handle.net/1721.1/62632 |
| _version_ | 1826198162078957568 |
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| author | Camiña, Steven L |
| author2 | Stuart Madnick and Wei Lee Woon. |
| author_facet | Stuart Madnick and Wei Lee Woon. Camiña, Steven L |
| author_sort | Camiña, Steven L |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. |
| first_indexed | 2024-09-23T11:00:10Z |
| format | Thesis |
| id | mit-1721.1/62632 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:00:10Z |
| publishDate | 2011 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/626322019-04-12T12:55:39Z A comparison of taxonomy generation techniques using bibliometric methods : applied to research strategy formulation Camiña, Steven L Stuart Madnick and Wei Lee Woon. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 86-87). This paper investigates the modeling of research landscapes through the automatic generation of hierarchical structures (taxonomies) comprised of terms related to a given research field. Several different taxonomy generation algorithms are discussed and analyzed within this paper, each based on the analysis of a data set of bibliometric information obtained from a credible online publication database. Taxonomy generation algorithms considered include the Dijsktra-Jamik-Prim's (DJP) algorithm, Kruskal's algorithm, Edmond's algorithm, Heymann algorithm, and the Genetic algorithm. Evaluative experiments are run that attempt to determine which taxonomy generation algorithm would most likely output a taxonomy that is a valid representation of the underlying research landscape. by Steven L. Camiña. M.Eng. 2011-05-09T15:11:46Z 2011-05-09T15:11:46Z 2010 2010 Thesis http://hdl.handle.net/1721.1/62632 712959766 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 108 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Camiña, Steven L A comparison of taxonomy generation techniques using bibliometric methods : applied to research strategy formulation |
| title | A comparison of taxonomy generation techniques using bibliometric methods : applied to research strategy formulation |
| title_full | A comparison of taxonomy generation techniques using bibliometric methods : applied to research strategy formulation |
| title_fullStr | A comparison of taxonomy generation techniques using bibliometric methods : applied to research strategy formulation |
| title_full_unstemmed | A comparison of taxonomy generation techniques using bibliometric methods : applied to research strategy formulation |
| title_short | A comparison of taxonomy generation techniques using bibliometric methods : applied to research strategy formulation |
| title_sort | comparison of taxonomy generation techniques using bibliometric methods applied to research strategy formulation |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/62632 |
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