Robust Character Recognition of Gray-Scaled Images with Graphical Designs and Noise
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
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
Hierarchy extraction based on inclusion of appearance
ACLdemo '04 Proceedings of the ACL 2004 on Interactive poster and demonstration sessions
Construction of an objective hierarchy of abstract concepts via directional similarity
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Related Word Lists Effective in Creativity Support
IEICE - Transactions on Information and Systems
Extracting word sets with non-taxonomical relation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Acquiring concept hierarchies of adjectives from corpora
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
Extracting term collocations for directing users to informative web pages
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
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In this paper, we propose a method of automatically extracting word hierarchies based on the inclusion relations of word appearance patterns in corpora. We applied the complementary similarity measure (CSM) to determine a hierarchical structure of word meanings. The CSM is a similarity measure developed for recognizing degraded machine-printed text. There are CSMs for both binary and gray-scale images. The CSM for binary images has been applied to estimate one-to-many relations, such as superordinate-subordinate relations, and to extract word hierarchies. However, the CSM for gray-scale images has not been applied to natural language processing. Here, we apply the latter to extract word hierarchies from corpora. To do this, we used frequency information for co-occurring words, which is not considered when using the CSM for binary images. We compared our hierarchies with those obtained using the CSM for binary images, and evaluated them by measuring their degree of agreement with the EDR electronic dictionary.