Abstract
We outline a learning framework that aims at identifying useful contextual cues for knowledge-based word sense disambiguation. The usefulness of individual context words is evaluated based on diverse lexico-statistical and syntactic information, as well as simple word distance. Experiments using two different knowledge-based methods and benchmark datasets show significant improvements due to context modeling, beating the conventional window-based approach.
Original language | English |
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Title of host publication | Conference Proceedings - EMNLP 2015 |
Subtitle of host publication | Conference on Empirical Methods in Natural Language Processing |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 1662-1667 |
Number of pages | 6 |
ISBN (Electronic) | 9781941643327 |
DOIs | |
State | Published - 2015 |
Event | Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Lisbon, Portugal Duration: 17 Sep 2015 → 21 Sep 2015 |
Publication series
Name | Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing |
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Conference
Conference | Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 |
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Country/Territory | Portugal |
City | Lisbon |
Period | 17/09/15 → 21/09/15 |
Bibliographical note
Publisher Copyright:© 2015 Association for Computational Linguistics.
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Science Applications
- Information Systems