Paper: Inducing Ontological Co-Occurrence Vectors

ACL ID P05-1016
Title Inducing Ontological Co-Occurrence Vectors
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005
  • Patrick Pantel (University of Southern California, Marina del Rey CA)

In this paper, we present an unsupervised methodology for propagating lexical co- occurrence vectors into an ontology such as WordNet. We evaluate the framework on the task of automatically attaching new concepts into the ontology. Experimental results show 73.9% attachment accuracy in the first position and 81.3% accuracy in the top-5 positions. This framework could potentially serve as a foundation for on- tologizing lexical-semantic resources and assist the development of other large- scale and internally consistent collections of semantic information.