Thesaurus-based efficient example retrieval by generating retrieval queries from similarities

Authors:
Takehito Utsuro;Kiyotaka Uchimoto;Mitsutaka Matsumoto;Makoto Nagao
Affiliations:
Nara Institute of Science and Technology;Kyoto University;Kyoto University;Kyoto University
Venue:
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Year:
1994

Citing 2
Cited 3

A framework of a mechanical translation between Japanese and English by analogy principle

Proc. of the international NATO symposium on Artificial and human intelligence
Toward memory-based translation

COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3

Review Article: Example-based Machine Translation

Machine Translation
Selective sampling for example-based word sense disambiguation

Computational Linguistics
Panning for EBMT gold, or "Remembering not to forget"

Machine Translation

Quantified Score

Hi-index	0.00

Visualization

Abstract

In example-based NLP, the problem of computational cost of example retrieval is severe, since the retrieval time increases in proportion to the number of examples in the database. This paper proposes a novel example retrieval method for avoiding full retrieval of examples. The proposed method has the following three features, 1) it generates retrieval queries from similarities, 2) efficient example retrieval through the tree structure of a thesaurus, 3) binary search along subsumption ordering of retrieval queries. Example retrieval time drastically decreases with the method.