Similarity Detection Based on Semantic Distance

Combining basic language processing methodologies with the conceptual framework of WordNet, semantic distance is used to measure the similarity between documents. Noun and verb word concepts are transformed into paths that represent their physical location within the WordNet hierarchy. Path prefixes are compared using three distinct algorithms-each investigates a particular type of semantic distance. The results suggest that similarity can be derived from a conceptual hierarchy. The key to finding similarity lies in its precise definition.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Computer Science

Grantor

Texas State University-San Marcos

Year dc:date.issued

2007

Author dc:creator

• Adams, Kimberly E.

Advisor dc:contributor.advisor

• East, Deborah

• conceptual structures
• programming languages
• information theory
• electronic computers
• semantics

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10877/8816

OAI identifier oai:identifier

oai:digital.library.txst.edu:10877/8816