A Comparison of Statistical Filtering Methods for Automatic Term Extraction for Domain Analysis

Fourteen word frequency metrics were tested to evaluate their effectiveness in identifying vocabulary in a domain. Fifteen domain engineering projects were examined to measure how closely the vocabularies selected by the fourteen word frequency metrics were to the vocabularies produced by domain engineers. Six filtering mechanisms were also evaluated to measure their impact on selecting proper vocabulary terms. The results of the experiment show that stemming and stop word removal do improve overlap scores and that term frequency is a valuable contributor to overlap. Variations on term frequency are not always significant improvers of overlap.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science

Department dc:contributor.department

Computer Science

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2008

Author dc:creator

• Tilley, Jason W.

Chair dc:contributor.committeechair

• Frakes, William B.

Committee members dc:contributor.committeemember

• Kulczycki, Gregory W.
• Belli, Gabriella M.

• domain analysis
• term extraction

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

etd-01052009-103100

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/30818