A fuzzy model for NMT word alignment using quasi-perfect matching
Küçük Resim Yok
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Heidelberg
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this article, first, the concept of quasi-perfect matching in a fuzzy graph is introduced. In addition to using these types of matching in expressing our main application goal, this introduction provides a complete classification on all matching that are known as maximum matching in classical graph theory. A useful set called conductive set has been obtained to be able to customize any of the introduced categories for matchings as desired or according to the practical necessity. Extensions with different powers are made from a fuzzy graph and useful meters are generated on each of them. These extensions and related concepts have been used in a different approach for words alignment in machine translation. The mismatch between the number of sentence words in the source and target languages has always been a challenge for the designers of machine translation systems in word-based alignment. To solve this, we introduce a different approach for aligning words, based on a fuzzy graph extracted from a parallel corpus.
Açıklama
Anahtar Kelimeler
Conductive Set, Words Alignment, Quasi-Perfect Matching, Self-Perfect Matching
Kaynak
Computational & Applied Mathematics
WoS Q Değeri
N/A
Scopus Q Değeri
Q2
Cilt
42
Sayı
8
