Interactive feature space construction using semantic information

Dan Roth, Kevin Small

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Specifying an appropriate feature space is an important aspect of achieving good performance when designing systems based upon learned classifiers. Effectively incorporating information regarding semantically related words into the feature space is known to produce robust, accurate classifiers and is one apparent motivation for efforts to automatically generate such resources. However, naive incorporation of this semantic information may result in poor performance due to increased ambiguity. To overcome this limitation, we introduce the interactive feature space construction protocol, where the learner identifies inadequate regions of the feature space and in coordination with a domain expert adds descriptiveness through existing semantic resources. We demonstrate effectiveness on an entity and relation extraction system including both performance improvements and robustness to reductions in annotated data.

Original languageEnglish (US)
Title of host publicationCoNLL 2009 - Proceedings of the Thirteenth Conference on Computational Natural Language Learning
PublisherAssociation for Computational Linguistics (ACL)
Pages66-74
Number of pages9
ISBN (Print)1932432299, 9781932432299
DOIs
StatePublished - 2009
Event13th Conference on Computational Natural Language Learning, CoNLL 2009 - Boulder, CO, United States
Duration: Jun 4 2009Jun 5 2009

Publication series

NameCoNLL 2009 - Proceedings of the Thirteenth Conference on Computational Natural Language Learning

Other

Other13th Conference on Computational Natural Language Learning, CoNLL 2009
Country/TerritoryUnited States
CityBoulder, CO
Period6/4/096/5/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Linguistics and Language

Fingerprint

Dive into the research topics of 'Interactive feature space construction using semantic information'. Together they form a unique fingerprint.

Cite this