• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.616-619
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• 1988

This paper deals with a semantic properties of Korea noun for semantic process in machine translation. The procedure is carried out as follow; 1) 17,000 words of Korean nouns are collected. 2) Semantic category is classifed into 39 markers. 3) We slow the redundancy of semantic properties and improve the efficiency of dictionary by marking the hierarchical concept structure.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.75-83
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• 2018

Multicultural family members have difficulty in educating their children due to language differences. In order to solve these difficulties, it is necessary to provide smart translation services that enable them easily and quickly access real-life vocabularies. However, the current automatic translation technology is being developed in dominant languages such as English, Chinese, and Japanese. There are also limitations to translating special-purpose terms such as documents of schools and instructions of public institutions. In this study, we propose a real-time automatic word translation service for multicultural family members who understand beginner level Korean. The service automatically analyzes the semantics of each word in the Korean sentences and provides a word-by-word translation. This study includes semantic analysis research for Korean language, building multilingual translation knowledge, and fusion study of language education. We evaluated the word translation service for migrant women from Vietnam and Japan and obtained meaningful evaluation results.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.953-957
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• 2009

This paper proposes a keyword-based query translation system for the semantic web. With the relationship between keywords and ontology structure information, the system converts keyword based queries into queries written by formal query language which is appropriate for the semantic web. As a result, casual web users could not only express queries easily but also obtain the better result.

• International Journal of Contents
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• v.2 no.3
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• pp.1-5
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• 2006

Intelligent Content is defined as detailed information or fragment of content which contains a semantic data structure. This semantic structure makes possible to do various intelligent operations. There are wide range of content-oriented applications such as classification, retrieval, extraction, translation, presentation and question-answering. The concept of Intelligent Content is applied to various fields like MPEG and Semantic Web. In this paper, we discuss the several important researches of Intelligent Content and how to apply this conception to these fields.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.2
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• pp.56-61
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• 2000

The quality of English to Korean Machine Translation depends on how well it deals with target word selection of verbs containing enormous ambiguity. Verb sense disambiguation can be done by using collocation, but the construction of verb collocations costs a lot of efforts and expenses. So, existing methods should be examined in the practical view points. This paper describes the practical method of target word selection using existing collocation and semantic distance computed from minimum semantic features of nouns.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.4
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• pp.509-515
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• 2007

Purpose: The purpose of this study was to translate and validate the Korean version of Hall's Professional Inventory(HPI) scale to assess levels of professionalism among Korean registered nurses. Method: The 25 item HPI scale was translated and content review was done by translation panel. After the content review, a bilingual nursing scholar performed the back-translation into English. A semantic equivalence test was conducted with 5 American nursing professors. A pilot study was conducted with a sample of 164 registered nurses in Korea to test the validity and reliability of the translated HPI. Result: The content equivalence for translated version of HPI was validated by a translation panel. The finding of the semantic equivalence test of back-translated version was 72.8%. The Cronbach's alpha for the Korean version of HPI was .820. Conclusions: This study provides information about the issues of translating an instrument such as the HPI. The Korean version of the HPI is a valid and reliable instrument and can have psychometric properties equivalent to those of the original HPI. The translated version could be used for assessing levels of professionalism for other health care professionalism as well as nurses.

• Annual Conference on Human and Language Technology
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• 2014.10a
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• pp.38-43
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• 2014

본 논문은, 현존하는 영어 FrameNet 데이터를 기반으로 하여, FrameNet에 대한 전문 지식이 없는 번역가들을 통해 수행할 수 있는 한국어 FrameNet의 수동 구축 개발 과정을 제시한다. 우리 연구팀은 실제로, NLTK가 제공하는 영어 FrameNet 버전 1.5의 Full Text를 이루고 있는 5,945개의 문장들 중에서, Frame 데이터를 가진 4,025개의 문장들을 추출해내어, 번역가들에 의해 한국어로 수동번역 함으로써, 한국어 FrameNet 구축 개발을 향한 의미 있는 초석을 마련하였으며, 제시한 방법의 실효성을 입증하는 연구결과들을 웹에 공개하기도 하였다.

• Language and Information
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• v.2 no.1
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• pp.1-41
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• 1998

Evaluation of multilingual translation fundamentally involves measurement of meaning equivalences between the formally mapped discourses/texts of SL(source language) and TL(target language) both represented by a metalanguage called IL(interlingua). Unlike a usaal uni-directional MT(machine translation) model(e.g.:SL $\rightarrow$ analysis $\rightarrow$ transfer $\rightarrow$ generation $\rightarrow$ TL), a bi-directional(by 'negotiation') model(i.e.: SL $\rightarrow$ IL/S $\leftrightarrow$ IL $\leftrightarrow$ IL/T \leftarrow TL) is proposed here for the purpose of evaluating multilingual, not merely bilingual, translation. The IL, as conceived of in this study, is an English-based predicate logic represented in the framework of MRS(minimal recursion semantics), an MT-oriented off-shoot of HPSG(Head-driven Phrase Structure Grammar). In addition, a list of semantic and pragmatic checkpoints are set up, some being optional depending on the kind and use of the translation, so sa to have the evaluation of translation fine-grained by computing matching or mismatching of such checkpoints.

• Korean Journal of Cognitive Science
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• v.19 no.2
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• pp.177-203
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• 2008

The present study was aimed to compare the semantic systems represented by the lexicon between L1 and L2 in late Korean-English bilinguals. The participants performed the word-picture matching task. the task was to decide whether the pictures represent the previously presented words' meaning. The words were the basic level categories. The stimuli were consisted of common object belonged to two different semantic categories (natural and artificial). To control the translation strategies, the SOA were manipulated as 650ms(Exp. 1) and 250ms(Exp. 2). No translation effort was found in the comparison of the two experiments. In both experiment, the RTs were faster in L1 rendition, and it took longer to decide the stimuli in natural categories than with artificial ones in L1. However, this category effect was not observed in L2. The results showed the differences in the organization of semantic representations in the brain through the bilinguals' two languages. While L1 semantic knowledge might be more systematically organized, that of L2 seems to be less well organized, at least by late bilinguals who participated in the present study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1919-1925
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• 2022

In this paper, we propose an image-to-image translation approach based on the conditional generative adversarial network for semantic segmentation. Semantic segmentation is the task of clustering parts of an image together which belong to the same object class. Unlike the traditional pixel-wise classification approach, the proposed method parses an input RGB image to its corresponding semantic segmentation mask using a pixel regression approach. The proposed method is based on the Pix2Pix image synthesis method. We employ residual connections-based convolutional neural network architectures for both the generator and discriminator architectures, as the residual connections speed up the training process and generate more accurate results. The proposed method has been trained and tested on the NYU-depthV2 dataset and could achieve a good mIOU value (49.5%). We also compare the proposed approach to the current methods in semantic segmentation showing that the proposed method outperforms most of those methods.