Acquiring concept hierarchies of adjectives from corpora

Authors:
Kyoko Kanzaki;Qing Ma;Eiko Yamamoto;Tamotsu Shirado;Hitoshi Isahara
Affiliations:
National Institute of Information and Communications Technology, Kyoto, Japan;Ryukoku University, Seta, Otsu, Japan;National Institute of Information and Communications Technology, Kyoto, Japan;National Institute of Information and Communications Technology, Kyoto, Japan;National Institute of Information and Communications Technology, Kyoto, Japan
Venue:
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
Year:
2006

Citing 11
Cited 0

Foundations of statistical natural language processing

Foundations of statistical natural language processing
Self-Organizing Maps

Self-Organizing Maps
Towards the automatic identification of adjectival scales: clustering adjectives according to meaning

ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Noun classification from predicate-argument structures

ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Automatic acquisition of hyponyms from large text corpora

COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Finding parts in very large corpora

ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Automatic construction of a hypernym-labeled noun hierarchy from text

ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Concept discovery from text

COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Inducing German semantic verb classes from purely syntactic subcategorisation information

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Self-organizing semantic maps and its application to word alignment in Japanese-Chinese parallel corpora

Neural Networks - 2004 Special issue: New developments in self-organizing systems
Extraction of hierarchies based on inclusion of co-occurring words with frequency information

IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

We describe a method to acquire a distribution of the concepts of adjectives automatically by using a self-organizing map and a directional similarity measure. A means of evaluating concept hierarchies of adjectives extracted automatically from corpora is elucidated. We used Scheffe's method of paired comparison to test experimentally the validity of hierarchies thus obtained with human intuition and found that our method was effective for 43% of the hierarchies considered.