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Semantic associative network for text analysis (SANTA)
| dc.creator | Airhart, Robert William | |
| dc.date.accessioned | 2012-06-07T22:58:19Z | |
| dc.date.available | 2012-06-07T22:58:19Z | |
| dc.date.created | 2000 | |
| dc.date.issued | 2000 | |
| dc.identifier.uri | https://hdl.handle.net/1969.1/ETD-TAMU-2000-THESIS-A385 | |
| dc.description | Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item. | en |
| dc.description | Includes bibliographical references (leaves 62-64). | en |
| dc.description | Issued also on microfiche from Lange Micrographics. | en |
| dc.description.abstract | Based on theories of associations, the Semantic Associative Network for Text Analysis (SANTA) has been developed. Nodes in the network represent words and links between nodes represent the association strengths between them. The links are adjusted by a learning function based on the co-occurrence of the words. Given textual samples, SANTA can determine which words have greater association. Using this information, semantic keywords for text can be suggested and textual similarity can be determined. As the number of samples increases, so does the need for finding relevant documents. In line with this need, the ability to find relevant documents increases since better associations are learned given the additional samples. Ostensive retrieval is the goal in that searching for documents is initiated by first presenting a relevant item. Keyword searching is also available. Evaluations of SANTA suggest much promise for this approach. | en |
| dc.format.medium | electronic | en |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en_US | |
| dc.publisher | Texas A&M University | |
| dc.rights | This thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use. | en |
| dc.subject | computer science. | en |
| dc.subject | Major computer science. | en |
| dc.title | Semantic associative network for text analysis (SANTA) | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | computer science | en |
| thesis.degree.name | M.S. | en |
| thesis.degree.level | Masters | en |
| dc.type.genre | thesis | en |
| dc.type.material | text | en |
| dc.format.digitalOrigin | reformatted digital | en |
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