• Title/Summary/Keyword: Korean Natural Language Processing

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A Natural Language Conversation Method for Intelligent NPC Implementation in Games (게임에서의 지능적 NPC 구현을 위한 자연어 대화 처리 기법)

  • Woo, Young-Woon;Park, Sung-Dae;Park, Choong-Shik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.12
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    • pp.2406-2412
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    • 2007
  • Recently, there are many researches about natural language processing programs using artificial intelligence methods. But the researches mostly concentrate on Korean morphological analyses and there are few researches about application of the results of Korean morphological analyses. In this paper, we implemented a natural language conversation program that NPC in games can talk with users by natural language sentences using the results of morphological analyses and a rule-based inference method. We proposed representation and implementation methods of rules suitable for the processing of natural language conversation using NEO, a rule-based inference engine. In the experiment using rules and facts about knowledge of conversation for diet counselor NPC, we could verify that natural conversation results were produced.

A BERT-Based Automatic Scoring Model of Korean Language Learners' Essay

  • Lee, Jung Hee;Park, Ji Su;Shon, Jin Gon
    • Journal of Information Processing Systems
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    • v.18 no.2
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    • pp.282-291
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    • 2022
  • This research applies a pre-trained bidirectional encoder representations from transformers (BERT) handwriting recognition model to predict foreign Korean-language learners' writing scores. A corpus of 586 answers to midterm and final exams written by foreign learners at the Intermediate 1 level was acquired and used for pre-training, resulting in consistent performance, even with small datasets. The test data were pre-processed and fine-tuned, and the results were calculated in the form of a score prediction. The difference between the prediction and actual score was then calculated. An accuracy of 95.8% was demonstrated, indicating that the prediction results were strong overall; hence, the tool is suitable for the automatic scoring of Korean written test answers, including grammatical errors, written by foreigners. These results are particularly meaningful in that the data included written language text produced by foreign learners, not native speakers.

Verb Pattern Based Korean-Chinese Machine Translation System

  • Kim, Changhyun;Kim, Young-Kil;Hong, Munpyo;Seo, Young-Ae;Yang, Sung-Il;Park, Sung-Kwon
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2002.02a
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    • pp.157-165
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    • 2002
  • This paper describes our ongoing Korean-Chinese machine translation system, which is based on verb patterns. A verb pattern consists of a source language pattern part for analysis and a target language pattern part for generation. Knowledge description on lexical level makes it easy to achieve accurate analyses and natural, correct generation. These features are very important and effective in machine translation between languages with quite different linguistic structures including Korean and Chinese. We performed a preliminary evaluation of our current system and reported the result in the paper.

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Method for Detecting Errors of Korean-Chinese MT Using Parallel Corpus (병렬 코퍼스를 이용한 한중 기계번역 오류 탐지 방법)

  • Jin, Yun;Kim, Young-Kil
    • Annual Conference on Human and Language Technology
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    • 2008.10a
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    • pp.113-117
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    • 2008
  • 본 논문에서는 패턴기반 자동번역시스템의 효율적인 번역 성능 향상을 위해 병렬 코퍼스(parallel corpus)를 이용한 오류 자동 탐지 방법을 제안하고자 한다. 번역시스템에 존재하는 대부분 오류는 크게 지식 오류와 엔진 오류로 나눌 수 있는데 통상 이런 오류는 이중 언어가 가능한 훈련된 언어학자가 대량의 자동번역 된 결과 문장을 읽음으로써 오류를 탐지하고 분석하여 번역 지식을 수정/확장하거나 또는 엔진을 개선하게 된다. 하지만, 이런 작업은 많은 시간과 노력을 필요로 하게 된다. 따라서 본 논문에서는 병렬 코퍼스 중의 목적 언어(Target Language) 문장 즉, 정답 문장과 자동번역 된 결과 문장을 다양한 방법으로 비교하면서 번역시스템에 존재하고 있는 지식 및 엔진 오류를 자동으로 탐지하는 방법을 제안한다. 제안한 방법은 한-중 자동번역시스템에 적용하여 그 정확률과 재현률을 측정하였으며, 자동적으로 오류를 탐지하여 추출 할 수 있음을 증명하였다.

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YDK : A Thesaurus Developing System for Korean Language (한국어 통합정보사전 시스템)

  • Hwang, Do-Sam;Choi, Key-Sun
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.9
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    • pp.2885-2893
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    • 2000
  • Dictionaries are indispensable for NLP(natural language processing) systems. Sophisticated algorithms in the NLP systems can be fully appreciated only with matching dictionaries that are built systematically based on computational linguistics. Only few dictionaries are developed for natural language processing. Available dictionaries are far from complete specifications for practical uses. So, it is necessary to develop an integrated information dictionary that includes useful lexical information for processing and understanding natural languages such as morphology and syntactic and semantic information. In this paper, we propose a method to build an integrated dictionary, and introduce a dictionary developing system.

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Application of Natural Language Processing(2):The Natural Language Interface for an Intelligent Geography Tutoring System. (자연어 활용(2):지능형 지리교육 시스템을 위한 자연어 인터 페이스에 관한 연구)

  • 장덕성;김승광
    • Korean Journal of Cognitive Science
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    • v.3 no.2
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    • pp.291-309
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    • 1992
  • The computer manipulation by means of natural language prcessing will be not only helpful to use the computer with more simple and more comfortable but also flexiable to communicate between human and computers.In this paper the natural language interfaces will be applied to an intelligent geography tutoring systems(IGTS),and we will inspect the something to consider in the case of its implementation.Each module of IGTS is connected to the interface module and correspondence with each other for the sake of natural conversation between system and learner.

A Research on Test Suites for Machine Translation Systems. (기계번역 시스템 측정 장치 연구)

  • Lee, Min-Haeng;Jee, Kwang-Sin;Chung, So-Woo
    • Language and Information
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    • v.2 no.2
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    • pp.185-220
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    • 1998
  • The purpose of this research is to propose a set of basic guidelines for the construction of English test suites, a set of basic guidelines for the construction of Korean test suites to objectively evaluate the performance of machine translation systems. For this end, we constructed 650 English test sentences, 650 Korean test sentences, and developed the statistical methods and tools for the comparative evaluation of the English-Korean machine translation systems. It also evaluates the existing commercial English-Korean machine translation systems. The importance of this research lies in that it will promote an awareness of the importance and need of testing machine translation systems within the Natural Language Community. This research will also make a big contribution to the development of evaluation methods and techniques for appropriate test suites for Korean information processing systems. The results of this research can be used by the natural language community to test the performance and development of their information processing systems or machine translation systems.

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KOREAN TOPIC MODELING USING MATRIX DECOMPOSITION

  • June-Ho Lee;Hyun-Min Kim
    • East Asian mathematical journal
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    • v.40 no.3
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    • pp.307-318
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    • 2024
  • This paper explores the application of matrix factorization, specifically CUR decomposition, in the clustering of Korean language documents by topic. It addresses the unique challenges of Natural Language Processing (NLP) in dealing with the Korean language's distinctive features, such as agglutinative words and morphological ambiguity. The study compares the effectiveness of Latent Semantic Analysis (LSA) using CUR decomposition with the classical Singular Value Decomposition (SVD) method in the context of Korean text. Experiments are conducted using Korean Wikipedia documents and newspaper data, providing insight into the accuracy and efficiency of these techniques. The findings demonstrate the potential of CUR decomposition to improve the accuracy of document clustering in Korean, offering a valuable approach to text mining and information retrieval in agglutinative languages.

A Study on the Construction of Database contains Knowledge for the Structural Design using the Natural Language Processing (자연어처리를 이용한 구조물 설계지식정보 데이터베이스 구축에 관한연구)

  • 이민호;이정재;김한중;윤성수
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 1999.10c
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    • pp.245-251
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    • 1999
  • In this study, by using the natural language processing of the field artificial intelligence, automated index was performed . And then, the Natural Language Processor for Constructing Database (NALPDB) has been developed. Furthermore, the Design knowldege Information Relational DataBase (DIREDB) has been also developed, which is designed to interlock the knowledge base. DIREDB processes both the documented design-data , like a concrete standard specification, and the design knowledge frrom an expert. DIREDB is also simulates the design space of structures accordance with the production rule, and thus it is determined that DIREDB can be used as a engine to retrieve new knowledge and to implement knowldege base that is necessary to the development of automatic design system.

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Korean Semantic Annotation on the EXCOM Platform

  • Chai, Hyun-Zoo;Djioua, Brahim;Priol, Florence Le;Descles, Jean-Pierre
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2007.11a
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    • pp.548-556
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    • 2007
  • We present an automatic semantic annotation system for Korean on the EXCOM (EXploration COntextual for Multilingual) platform. The purpose of natural language processing is enabling computers to understand human language, so that they can perform more sophisticated tasks. Accordingly, current research concentrates more and more on extracting semantic information. The realization of semantic processing requires the widespread annotation of documents. However, compared to that of inflectional languages, the technology in agglutinative language processing such as Korean still has shortcomings. EXCOM identifies semantic information in Korean text using our new method, the Contextual Exploration Method. Our initial system properly annotates approximately 88% of standard Korean sentences, and this annotation rate holds across text domains.

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