Mining class association rules for word sense disambiguation

Authors:
Ł/ukasz Kobyli$#324/ski
Affiliations:
Institute of Computer Science, Polish Academy of Sciences, Warszawa, Poland
Venue:
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
Year:
2011

Citing 11
Cited 0

Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone

SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Mining Constrained Association Rules to Predict Heart Disease

ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases

VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Learning Rules for Large-Vocabulary Word Sense Disambiguation: A Comparison of Various Classifiers

NLP '00 Proceedings of the Second International Conference on Natural Language Processing
Text Document Categorization by Term Association

ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Introduction to the special issue on word sense disambiguation: the state of the art

Computational Linguistics - Special issue on word sense disambiguation
Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)

Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)
Personalizing PageRank for word sense disambiguation

EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
SemEval-2007 task 17: English lexical sample, SRL and all words

SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
The WSD development environment

LTC'09 Proceedings of the 4th conference on Human language technology: challenges for computer science and linguistics

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we propose an approach to the task of Word Sense Disambiguation problem that uses Class Association Rules to create an effective and human-understandable rule-based classifier. We present the accuracy of classification of selected polysemous words on an evaluation corpus using the proposed method and compare it to other known approaches. We discuss the advantages and weaknesses of a classifier based on association rules and present ideas for future work on the idea.