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pro vyhledávání: '"Konstantinos Chatzitheodorou"'
Publikováno v:
Syn-Thèses, Vol 0, Iss 5, Pp 111-120 (2012)
Machine Translation (MT) evaluation is a hard task considering the difficulties that raise from the translation process itself. In this paper we present the results of the evaluation of a Statistical Machine Translation (SMT) system in which the Mose
Externí odkaz:
https://doaj.org/article/9e4fa3584a0b47089d4772bbc295f780
Publikováno v:
Developments in Cognitive Translation and Interpreting Studies. 8:378-403
The working environment of translators has changed significantly in recent decades, with post-editing (PE) emerging as a new trend in the human translation workflow, particularly following the advent of neural machine translation (NMT) and the improv
Publikováno v:
Mathematical Models in Engineering, Vol 7, Iss 1, Pp 1-9 (2021)
In this paper, we present an advanced domain-specific multi-word terminology extraction method. Our hybrid approach for automatic term identification benefits from both statistical and linguistic approaches. Our main goal is to reduce as much as poss
Publikováno v:
Vibroengineering PROCEDIA. 34:20-26
In this paper, we present the initial results of a terminology study on a vibration-based condition monitoring technique to support the research community. We automatically export terminologies from domain specific textual corpora and a team of subje
Autor:
Konstantinos Chatzitheodorou
Publikováno v:
The Prague Bulletin of Mathematical Linguistics. 100:83-89
A hotly debated topic in machine translation is human evaluation. On the one hand, it is extremely costly and time consuming; on the other, it is an important and unfortunately inevitable part of any system. This paper describes COSTA MT Evaluation T
Autor:
Konstantinos Chatzitheodorou
Publikováno v:
LG-LP@COLING
Support verb constructions (SVC), are verb-noun complexes which play a role in many natural language processing (NLP) tasks, such as Machine Translation (MT). They can be paraphrased with a full verb, preserving its meaning, improving at the same tim