Bootstrapping word sense disambiguation using dynamic web knowledge

Authors:
Yuanyong Wang;Achim Hoffmann
Affiliations:
School of Computer Science & Engineering, The University of New South Wales, Sydney, Australia;School of Computer Science & Engineering, The University of New South Wales, Sydney, Australia
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

Citing 4
Cited 1

An automatic method for generating sense tagged corpora

AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Introduction to the special issue on word sense disambiguation: the state of the art

Computational Linguistics - Special issue on word sense disambiguation
Unsupervised word sense disambiguation rivaling supervised methods

ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
A method for word sense disambiguation of unrestricted text

ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics

Web query disambiguation using PageRank

Journal of the American Society for Information Science and Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

Word Sense Disambiguation(WSD) is one of the traditionally most difficult problems in natural language processing and has broad theoretical and practical implications. One of the main difficulties for WSD systems is the lack of relevant knowledge-commonly known as the knowledge acquisition bottleneck problem. We present in this paper a novel method that utilizes dynamic Web data obtained through Web search engines to effectively enrich the semantic knowledge for WSD systems. We demonstrated through a word sense disambiguation system the large quantity and good quality of the extracted knowledge.