Machine Learning with Lexical Features: The Duluth Approach to Senseval-2

Ted Pedersen

Machine Learning with Lexical Features: The Duluth Approach to Senseval-2

Ted Pedersen

Computer Science (Duluth)

Research output: Contribution to journal › Conference article › peer-review

15 Scopus citations

Abstract

This paper describes the sixteen Duluth entries in the SENSEVAL-2 comparative exercise among word sense disambiguation systems. There were eight pairs of Duluth systems entered in the Spanish and English lexical sample tasks. These are all based on standard machine learning algorithms that induce classifiers from sense-tagged training text where the context in which ambiguous words occur are represented by simple lexical features. These are highly portable, robust methods that can serve as a foundation for more tailored approaches.

Original language	English (US)
Pages (from-to)	139-142
Number of pages	4
Journal	Proceedings of the Annual Meeting of the Association for Computational Linguistics
State	Published - 2001
Event	ACL 2001 2nd International Workshop on Evaluating Word Sense Disambiguation Systems, SENSEVAL@ACL 2001 - Toulouse, France Duration: Jul 5 2001 → Jul 6 2001

Bibliographical note

Publisher Copyright:
© 2001 Proceedings of the Annual Meeting of the Association for Computational Linguistics.

Find It

Find It at U of M Libraries

Cite this

@article{15cd7ce23f4e44dea2fa749ba3afb4de,

title = "Machine Learning with Lexical Features: The Duluth Approach to Senseval-2",

abstract = "This paper describes the sixteen Duluth entries in the SENSEVAL-2 comparative exercise among word sense disambiguation systems. There were eight pairs of Duluth systems entered in the Spanish and English lexical sample tasks. These are all based on standard machine learning algorithms that induce classifiers from sense-tagged training text where the context in which ambiguous words occur are represented by simple lexical features. These are highly portable, robust methods that can serve as a foundation for more tailored approaches.",

author = "Ted Pedersen",

note = "Publisher Copyright: {\textcopyright} 2001 Proceedings of the Annual Meeting of the Association for Computational Linguistics.; ACL 2001 2nd International Workshop on Evaluating Word Sense Disambiguation Systems, SENSEVAL@ACL 2001 ; Conference date: 05-07-2001 Through 06-07-2001",

year = "2001",

language = "English (US)",

pages = "139--142",

journal = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",

issn = "0736-587X",

publisher = "Association for Computational Linguistics (ACL)",

}

TY - JOUR

T1 - Machine Learning with Lexical Features

T2 - ACL 2001 2nd International Workshop on Evaluating Word Sense Disambiguation Systems, SENSEVAL@ACL 2001

AU - Pedersen, Ted

PY - 2001

Y1 - 2001

N2 - This paper describes the sixteen Duluth entries in the SENSEVAL-2 comparative exercise among word sense disambiguation systems. There were eight pairs of Duluth systems entered in the Spanish and English lexical sample tasks. These are all based on standard machine learning algorithms that induce classifiers from sense-tagged training text where the context in which ambiguous words occur are represented by simple lexical features. These are highly portable, robust methods that can serve as a foundation for more tailored approaches.

AB - This paper describes the sixteen Duluth entries in the SENSEVAL-2 comparative exercise among word sense disambiguation systems. There were eight pairs of Duluth systems entered in the Spanish and English lexical sample tasks. These are all based on standard machine learning algorithms that induce classifiers from sense-tagged training text where the context in which ambiguous words occur are represented by simple lexical features. These are highly portable, robust methods that can serve as a foundation for more tailored approaches.

UR - https://www.scopus.com/pages/publications/85149133535

UR - https://www.scopus.com/pages/publications/85149133535#tab=citedBy

M3 - Conference article

AN - SCOPUS:85149133535

SN - 0736-587X

SP - 139

EP - 142

JO - Proceedings of the Annual Meeting of the Association for Computational Linguistics

JF - Proceedings of the Annual Meeting of the Association for Computational Linguistics

Y2 - 5 July 2001 through 6 July 2001

ER -

Machine Learning with Lexical Features: The Duluth Approach to Senseval-2

Abstract

Bibliographical note

Find It

Other files and links

Fingerprint

Cite this