• Title/Summary/Keyword: language processing

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Development of E-Sports Application including Natural Language Processing-based Chatbot (자연어 처리 기반 챗봇이 포함된 E-스포츠 애플리케이션 개발)

  • Soojung Lee;Ye-Seong Ha;Gyeong-Hoon Jeong;Jin-Tae Seo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.501-502
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    • 2023
  • 본 논문은 자연어 처리(Natural Language Processing, NLP) 기술과 Flutter 언어를 활용하여 E-스포츠(E-Sports) 애플리케이션을 개발하는 방법을 제안한다. E-스포츠는 전 세계적으로 급속히 성장하는 산업이며, 많은 팬과 선수들이 참여하고 있다. 그러나 E-스포츠 관련 정보를 찾고 이해하기 위해서는 다양한 데이터를 직접 검색하고 분석해야 하는 어려움이 있다. 이러한 어려움을 극복하기 위해 자연어 처리 기술을 활용한 챗봇이 접목된 E-스포츠 애플리케이션을 개발하여 사용자가 효율적으로 관련 정보를 얻을 수 있도록 한다.

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Selecting Machine Learning Model Based on Natural Language Processing for Shanghanlun Diagnostic System Classification (자연어 처리 기반 『상한론(傷寒論)』 변병진단체계(辨病診斷體系) 분류를 위한 기계학습 모델 선정)

  • Young-Nam Kim
    • 대한상한금궤의학회지
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    • v.14 no.1
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    • pp.41-50
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    • 2022
  • Objective : The purpose of this study is to explore the most suitable machine learning model algorithm for Shanghanlun diagnostic system classification using natural language processing (NLP). Methods : A total of 201 data items were collected from 『Shanghanlun』 and 『Clinical Shanghanlun』, 'Taeyangbyeong-gyeolhyung' and 'Eumyangyeokchahunobokbyeong' were excluded to prevent oversampling or undersampling. Data were pretreated using a twitter Korean tokenizer and trained by logistic regression, ridge regression, lasso regression, naive bayes classifier, decision tree, and random forest algorithms. The accuracy of the models were compared. Results : As a result of machine learning, ridge regression and naive Bayes classifier showed an accuracy of 0.843, logistic regression and random forest showed an accuracy of 0.804, and decision tree showed an accuracy of 0.745, while lasso regression showed an accuracy of 0.608. Conclusions : Ridge regression and naive Bayes classifier are suitable NLP machine learning models for the Shanghanlun diagnostic system classification.

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An Experimental Comparison of the Usability of Rule-based and Natural Language Processing-based Chatbots

  • Yeji Lim;Jeonghun Lim;Namjae Cho
    • Asia pacific journal of information systems
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    • v.30 no.4
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    • pp.832-846
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    • 2020
  • Service organizations increasingly adopt data-based intelligent engines called chatbots in support of the interaction between customers and the companies. Two different types of chatbots have been suggested and introduced by companies leading the adoption of this emerging technology: rule-based chatbots and natural language processing-based chatbots. While the differences between these two types of technologies look relatively clear, the organizational and practical impacts of the differences have not been systematically explored. This study performed an experiment to compare the use of the two different types of chatbots used in practice by two comparable organizations. These two types of actual chatbots were used by Korean on-line shopping malls with similar business models (mobile shopping), length of history, size and reputation. The comparison was made based on such dimensions as usability, searchability, reliability and attractiveness. Contraty to conventional expectation that the superiority in technology will produce superior usability, the results show mixed superiority. The discussion on the reasons is presented.

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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Semi-Automatic Dialog Act Annotation based on Dialog Patterns (대화 패턴 기반 대화 의도 반자동 부착 방법)

  • Choi, Sung-Kwon;Jeong, Sang-Gun;Kim, Young-Gil
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.11a
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    • pp.1298-1301
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    • 2013
  • 대화 시스템에서 올바른 대화를 진행하기 위해서는 화자의 대화 의도를 파악하는 것이 중요하다. 특히 영어를 교육하기 위한 영어 교육용 대화 시스템에서는 학습자의 대화 의도 파악 오류가 발생할 경우 영어 교육에 문제가 발생하기 때문에 학습자의 대화 의도를 더욱 정확하게 분석 및 파악하는 것이 중요하다. 대화 패턴이란 시스템 발화에 대응되는 사용자 발화의 규칙적인 연쇄라고 할 수 있다. 대화 패턴 기반 대화 의도 부착 방법은 1) 대화 코퍼스 구축 2) 대화 시나리오에 있는 발화를 대상으로 기본 명사구 청킹(Base NP Chunking)을 하고 중심어(Head Word), 토픽 추적(Topic Tracking)에 의한 대화 패턴을 자동으로 추출한 후, 3) 대화 패턴 수동 검수이다. 대화 패턴 기반 대화 의도 부착 방법은 기본 명사구에 대한 지식만 가지고 있으면 대량으로 구축할 수 있다는 장점이 있다. 99 개의 대화 시나리오를 학습코퍼스로 하고 1 개의 대화 시나리오에 대해 대화턴 성공률을 시물레이션 한 결과 63.64%가 나왔다.

Neural Switching Mechanism in the late Korean-English bilinguals by Event-Related fMRI

  • Kim, Jeong-Seok
    • Journal of Biomedical Engineering Research
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    • v.29 no.4
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    • pp.272-277
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    • 2008
  • Functional MRI technique was used in this study for examining the language switching mechanisms between the first language (L1) and the second language (L2). Language switching mechanism is regarded as a complex task that involves an interaction between L1 and L2. The aim of study is to find out the brain activation patterns during the phonological process of reading real English words and English words written in Korean characters in a bilingual person. Korean-English bilingual subjects were examined while they covertly read four types of words native Korean words, Korean words of a foreign origin, English words written in Korean characters, and English words. The fMRI results reveal that the left hemispheric language-related regions at the brain, such as the left inferior frontal, superior temporal, and parietal cortices, have a greater response to the presentation of English words written in Korean characters than for the other types of words, in addition, a slight difference was observed in the occipital-temporal lobe. These results suggest that a change in the brain circuitry underlying the relational processes of language switching is mainly associated with general executive processing system in the left prefrontal cortex rather than with a similarity-based processing system in the occipital-temporal lobes.

Benchmarking of BioPerl, Perl, BioJava, Java, BioPython, and Python for Primitive Bioinformatics Tasks and Choosing a Suitable Language

  • Ryu, Tae-Wan
    • International Journal of Contents
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    • v.5 no.2
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    • pp.6-15
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    • 2009
  • Recently many different programming languages have emerged for the development of bioinformatics applications. In addition to the traditional languages, languages from open source projects such as BioPerl, BioPython, and BioJava have become popular because they provide special tools for biological data processing and are easy to use. However, it is not well-studied which of these programming languages will be most suitable for a given bioinformatics task and which factors should be considered in choosing a language for a project. Like many other application projects, bioinformatics projects also require various types of tasks. Accordingly, it will be a challenge to characterize all the aspects of a project in order to choose a language. However, most projects require some common and primitive tasks such as file I/O, text processing, and basic computation for counting, translation, statistics, etc. This paper presents the benchmarking results of six popular languages, Perl, BioPerl, Python, BioPython, Java, and BioJava, for several common and simple bioinformatics tasks. The experimental results of each language are compared through quantitative evaluation metrics such as execution time, memory usage, and size of the source code. Other qualitative factors, including writeability, readability, portability, scalability, and maintainability, that affect the success of a project are also discussed. The results of this research can be useful for developers in choosing an appropriate language for the development of bioinformatics applications.

A Study on the Design of an Elevator Driving Control Circuit Using SFC Language (SFC언어를 이용한 Elevator 운전 제어회로 설계에 관한 연구)

  • Lee Sang-mun;Kim Min-Chan;Kwak Gun-Pyong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.6
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    • pp.1260-1268
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    • 2005
  • Ladder Diagram(LD) is the most extensively used among PLC standard language for the design of control system. But LD has the disadvantages for data processing and maintenance. On the other hand, the Sequential Function Chart(SFC) graphic language is very powerful for describing the sequential logic control algorithm. SFC is based on flow chart, so control flow understanding is very easy and divergence can possible improving its ability. In this paper, we propose the efficient management elevator system using the action qualifiers and choice divergence. From the result, we confirm the SFC language reduced program memory capacity and processing time is faster than LD language.

Robust Sentiment Classification of Metaverse Services Using a Pre-trained Language Model with Soft Voting

  • Haein Lee;Hae Sun Jung;Seon Hong Lee;Jang Hyun Kim
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.9
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    • pp.2334-2347
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    • 2023
  • Metaverse services generate text data, data of ubiquitous computing, in real-time to analyze user emotions. Analysis of user emotions is an important task in metaverse services. This study aims to classify user sentiments using deep learning and pre-trained language models based on the transformer structure. Previous studies collected data from a single platform, whereas the current study incorporated the review data as "Metaverse" keyword from the YouTube and Google Play Store platforms for general utilization. As a result, the Bidirectional Encoder Representations from Transformers (BERT) and Robustly optimized BERT approach (RoBERTa) models using the soft voting mechanism achieved a highest accuracy of 88.57%. In addition, the area under the curve (AUC) score of the ensemble model comprising RoBERTa, BERT, and A Lite BERT (ALBERT) was 0.9458. The results demonstrate that the ensemble combined with the RoBERTa model exhibits good performance. Therefore, the RoBERTa model can be applied on platforms that provide metaverse services. The findings contribute to the advancement of natural language processing techniques in metaverse services, which are increasingly important in digital platforms and virtual environments. Overall, this study provides empirical evidence that sentiment analysis using deep learning and pre-trained language models is a promising approach to improving user experiences in metaverse services.

Natural Language Processing and Cognition (자연언어처리와 인지)

  • 이정민
    • Korean Journal of Cognitive Science
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    • v.3 no.2
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    • pp.161-174
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    • 1992
  • The present discussion is concerned with showing the development of natural language processing and how it is related to information and cognition.On the basis of the computeational model,in which humans are viewed as processors of linguistic structures that use stored knowledge-grammar, lexicon and structures representing the encyclopedic information of the world,such programs of natural language understanding as Winograd's SHRDLU came out.However,such pragmatic factors as contexts and the speaker's beliefs,internts,goals and intentions are not easy to process yet.Language,ingormation and cognition are argued to be closely interrelated,and the study of them,the paper argues,can lead to the development of science on general.