• Annual Conference on Human and Language Technology
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• 2014.10a
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• pp.167-172
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• 2014

본 논문에서는 한국어 자연언어처리 결과물들을 통일된 형식으로 표준화하기 위해서 NIF를 적용한 내용을 다룬다. 한국어 자연언어처리에 NIF 온톨로지를 적용한 이유와 적용과정에서 야기된 문제점들을 논의한다. 한국어 NLP2RDF 구축과정에서 한국어 자연언어처리에 필요한 새로운 클래스와 프로퍼티들을 추가로 정의하여 NIF 온톨로지를 변형 적용하였다.

• Language and Information
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• v.6 no.1
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• pp.123-138
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• 2002

This paper discusses issues in building a 54-thousand-word Korean Treebank using a phrase structure annotation, along with developing annotation guidelines based on the morpho-syntactic phenomena represented in the corpus. Various methods that were employed for quality control are presented. The evaluation on the quality of the Treebank and some of the NLP applications under development using the Treebank are also pre-sented.

• 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.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.57-66
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• 2022

Claims and disputes are major causes of cost and schedule overruns in the construction business. In order to manage claims and disputes effectively, it is necessary to analyze various types of contract documents punctually and accurately. Since volume of such documents is so vast, analyzing them in a timely manner is practically very challenging. Recently developed approaches such as artificial intelligence (AI), machine learning algorithms, and natural language processing (NLP) have been applied to various topics in the field of construction contract and claim management. Based on the systematic literature review, this paper analyzed the goals, methodologies, and application results of such approaches. AI methods applied to construction contract management are classified into several categories. This study identified possibilities and limitations of the application of such approaches. This study contributes to providing the directions for how such approaches should be applied to contract management for future studies, which will eventually lead to more effective management of claims and disputes.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.349-357
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• 2007

Named entities (NEs) are important in many Natural Language Processing (NLP) applications, and discovering NE-related relations in texts may be beneficial for these applications. This paper proposes a method to extract the ISA relation between a "named entity" and its category, and an IS-RELATED-TO relation between the category and its related object. Based on the pattern extraction algorithm "Person Category Extraction" (PCE), we extend it for solving our problem. Our experiments on Wall Street Journal (WSJ) corpus show promising results. We also demonstrate a possible application of these relations by utilizing them for semantic search.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.221-224
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• 2002

포항제철소에는 13개의 발전기가 있어 제철소에서 필요로 하는 전력을 자체적으로 945MWH 규모로 공급하고 있다. 발전소에서 사용되는 에너지원은 제철공정에서 부수적으로 발생하는 부생가스(BFG, COG, LDG, CFG)와 외부에서 구매하는 중유, LNG가 있다. 안정적인 전력공급과 비용절감을 위한 발전기 가동계획을 수립하기 위해서는, 조업상황에 따라 변동되는 전력소요량 및 부생가스 발생량을 예측하여 발전기별로 사용될 연료량을 배분하고, 발전기별 효율을 반영한 발전량을 결정하게 된다 이러만 발전기 가동계획 수립을 수작업에 의존하고 있어, 수시로 변화하는 상황에 신속한 대처가 곤란하고, 모든 요소를 고려하기가 어려워 에너지비용을 절감할 수 있는 기회손실의 우려가 있었다. 본 연구에서는 LP 및 NLP를 적응하여 발전기별 연료배분 및 발전량을 결정하는 과정을 자동적으로 수행하는 발전기 가동계획수립 Model을 개발하였다. Data 입·출력용으로 Excel, LP Package는 What's Best, Programming Language는 VBA(Visual Basic for Application)를 활용하였다.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.706-715
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• 2019

This research implemented grammatical rules for relationship extraction from class diagram candidate. The problem statement is generated by our algorithm to yield class diagram and candidate relationship candidates. The relationships of class diagrams are extracted automatically from the problem statement by using Natural Language Processing (NLP). The extraction used the grammatical rules that obtained from various sources and translated into our algorithm. The performance evaluation of the extraction algorithm used ATM problem statements. The application captures the problem statement and draws automatically the relations of class diagrams using Forced-Directionality Graph algorithm. The performance evaluations show refining methods for class diagram and relationships extraction improve recall score.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.9-17
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• 2019

As the artificial intelligence technology has developed recently, researches on chatbots that provide information and contents desired by users through an interactive interface have become active. Since chatbots require a variety of natural language processing technology and domain knowledge including typos and slang, it is currently limited to develop chatbots that can carry on daily conversations in a general-purpose domain. In this study, we propose an artificial intelligence chatbot that can provide real-time public traffic information and route information. The proposed chatbot has an advantage that it can understand the intention and requirements of the user through the conversation on the messenger platform without map application.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.386-394
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• 2019

This research will describe algorithm for class diagram extraction from problem statements. Class diagram notation consist of class name, attributes, and operations. Class diagram can be extracted from the problem statement automatically by using Natural Language Processing (NLP). The extraction results heavily depends on the algorithm and preprocessing stage. The algorithm obtained from various sources with additional rules that are obtained in the implementation phase. The evaluation features using five problem statement with different domains. The application will capture the problem statement and draw the class diagram automatically by using Windows Presentation Foundation(WPF). The classification accuracy of 100% was achieved. The final algorithm achieved 92 % of average precision score.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.144-150
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• 2023

With progressive advancements in Man-made consciousness (computer based intelligence) and Profound Learning (DL), contributing altogether to Normal Language Handling (NLP), the precision and nature of Machine Interpretation (MT) has worked on complex. There is a discussion, but that its no time like the present the human interpretation became immaterial or excess. All things considered, human flaws are consistently dealt with by its own creations. With the utilization of brain networks in machine interpretation, its been as of late guaranteed that keen frameworks can now decipher at standard with human interpreters. In any case, simulated intelligence is as yet not without any trace of issues related with handling of a language, let be the intricacies and complexities common of interpretation. Then, at that point, comes the innate predispositions while planning smart frameworks. How we plan these frameworks relies upon what our identity is, subsequently setting in a one-sided perspective and social encounters. Given the variety of language designs and societies they address, their taking care of by keen machines, even with profound learning abilities, with human proficiency looks exceptionally far-fetched, at any rate, for the time being.