Paper: Computing Semantic Similarity between Skill Statements for Approximate Matching

ACL ID N07-1072
Title Computing Semantic Similarity between Skill Statements for Approximate Matching
Venue Human Language Technologies
Session Main Conference
Year 2007
Authors
  • Feng Pan (University of Southern California, Marina del Rey CA)
  • Robert Farrell (IBM T.J. Watson Research Center, Yorktown Heights NY)

This paper explores the problem of com- puting text similarity between verb phrases describing skilled human behav- ior for the purpose of finding approximate matches. Four parsers are evaluated on a large corpus of skill statements extracted from an enterprise-wide expertise taxon- omy. A similarity measure utilizing com- mon semantic role features extracted from parse trees was found superior to an in- formation-theoretic measure of similarity and comparable to the level of human agreement.