• Title/Summary/Keyword: Language Resources

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Research and Development of a Geological Remote Sensing Information Extraction System

  • Zhengmin, He
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1275-1277
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    • 2003
  • This paper presents a geological remote sensing information extraction system, the aim of which is to provide practical models and powerful tools to extract geological information from remote sensing images for geological exploration applications. After reviewing and analyzing the existing methods for geological information extraction, we developed more than ten models to enhance and extract geological information, such as alteration information, linear features and special lithological characters. The system is developed based on Erdas Imagine using its programming language. It has been successfully used in the 'reat Investigation of Land and Natural Resources of China' program.

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QL2-XP Model for the Automatic Calibration in Water Quality Modeling (하천 수질 매개변수의 자동보정을 위한 QL2-XP 모형 개발)

  • Han, Kun-Yeun;Park, Kyung-Ok
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.474-477
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    • 2005
  • The Industrial development and the Increase in population have brought out a rapid increase of wastewater discharge. To deal with this matter, much estimate has been spend on construction and management of a large scale sewage treatment plant. Although every effort has been carried out, river water quality has no significantly improved. Especially. the aggravation of the water quality in dry season is brought out a serious social problem. The purpose of this study Is the development of an optimal water quality management technique considering the efficient control of the multiple pollutant load associated with the total pollutant load control. A GUI(Graphical User Interface) system named 'QL2-XP' model is developed by object-oriencted language for the user convenience and practical usage. Suggested GUI system consist of hydraulic analysis. water quality analysis, optimized model calibration processes, and postprocessing the simulation results.

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Internalization Problem in the Field of Library and Information Science in the People's Republic of China (중국 도서관학정보학 영역의 국제화 문제)

  • Duan Ming-lian
    • Journal of the Korean Society for Library and Information Science
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    • v.27
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    • pp.365-390
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    • 1994
  • The article sets forth a problem on international exchange and cooperation In the field of library and information science in the People's Republic of China from engles of academic and publication's exchange, It points out international exchange and cooperation between China and Korea should be developed from international exchange of publications and interlibrary loan to openning up standard, authority and current database on publications step by step. China and Korea should supply the database to all of the world, In order to come up to shared resources, the author has compared the Descriptive Cataloguing Rules for Western Language Materials, and the Bibliographical Description for Monographes with the Korean Cataloguing Rules for Description, and analyzed their different. In the end, the article presents the result that the documentation standardzation is the only way of accomplishing shared resources in the world from indentity of description for publications and materials, and unity of cataloguing rules.

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Research and Development of a Geological Remote Sensing Information Extraction System

  • Zhengmin, He
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1442-1444
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    • 2003
  • This paper presents a geological remote sensing information extraction system, the aim of which is to provide practical models and powerful tools to extract geological information from remote sensing images for geological exploration applications. After reviewing and analyzing the existing methods for geological information extraction, we developed more than ten models to enhance and extract geological information, such as alteration information, linear features and special lithological characters. The system is developed based on Erdas Imagine using its programming language. It has been successfully used in the ‘Great Investigation of Land and Natural Resources of China’ program.

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Towards cross-platform interoperability for machine-assisted text annotation

  • de Castilho, Richard Eckart;Ide, Nancy;Kim, Jin-Dong;Klie, Jan-Christoph;Suderman, Keith
    • Genomics & Informatics
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    • v.17 no.2
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    • pp.19.1-19.10
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    • 2019
  • In this paper, we investigate cross-platform interoperability for natural language processing (NLP) and, in particular, annotation of textual resources, with an eye toward identifying the design elements of annotation models and processes that are particularly problematic for, or amenable to, enabling seamless communication across different platforms. The study is conducted in the context of a specific annotation methodology, namely machine-assisted interactive annotation (also known as human-in-the-loop annotation). This methodology requires the ability to freely combine resources from different document repositories, access a wide array of NLP tools that automatically annotate corpora for various linguistic phenomena, and use a sophisticated annotation editor that enables interactive manual annotation coupled with on-the-fly machine learning. We consider three independently developed platforms, each of which utilizes a different model for representing annotations over text, and each of which performs a different role in the process.

Light Weight Korean Morphological Analysis Using Left-longest-match-preference model and Hidden Markov Model (좌최장일치법과 HMM을 결합한 경량화된 한국어 형태소 분석)

  • Kang, Sangwoo;Yang, Jaechul;Seo, Jungyun
    • Korean Journal of Cognitive Science
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    • v.24 no.2
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    • pp.95-109
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    • 2013
  • With the rapid evolution of the personal device environment, the demand for natural language applications is increasing. This paper proposes a morpheme segmentation and part-of-speech tagging model, which provides the first step module of natural language processing for many languages; the model is designed for mobile devices with limited hardware resources. To reduce the number of morpheme candidates in morphological analysis, the proposed model uses a method that adds highly possible morpheme candidates to the original outputs of a conventional left-longest-match-preference method. To reduce the computational cost and memory usage, the proposed model uses a method that simplifies the process of calculating the observation probability of a word consisting of one or more morphemes in a conventional hidden Markov model.

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The Interoperability between RDF/OWL and Topic Maps using the Semantic Wiki (시맨틱 위키를 이용한 RDF/OWL과 토픽맵 사이의 상호운용성)

  • Kim, Hoon-Min;Yang, Jung-Jin
    • The Journal of Society for e-Business Studies
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    • v.12 no.1
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    • pp.123-133
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    • 2007
  • With the emergence of Semantic Web and Web 2.0, the paradigm shift of the Web is on resource-centered services. That is, the focus now moves from having just rich resources to the meta-information of describing the resources. The relevant standards, RDF(Resource Description Language) and Topic Maps, of describing the meta-information are defined and adopted by W3C and ISO respectively. Describing meta-information in such a XML form could be burdensome to participants. Semantic Wiki extended from 1)WikiWikiWeb is proposed to deal with the problem. It enables users to generate RDF meta-information about Wiki pages with simple usages of the grammar. We discuss the way of improving interoperability between Topic Maps-based semantic Wiki papges and RDF-based ones. The method proposed by RDFTM task force is present with the usage of high-level Wiki grammar for facilitating low-level transformation.

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Korean consumers' perceptions of health/functional food claims according to the strength of scientific evidence

  • Kim, Ji-Yeon;Kang, Eun-Jin;Kwon, O-Ran;Kim, Gun-Hee
    • Nutrition Research and Practice
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    • v.4 no.5
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    • pp.428-432
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    • 2010
  • In this study, we investigated that consumers could differentiate between levels of claims and clarify how a visual aid influences consumer understanding of the different claim levels. We interviewed 2,000 consumers in 13 shopping malls on their perception of and confidence in different levels of health claims using seven point scales. The average confidence scores given by participants were 4.17 for the probable level and 4.07 for the possible level; the score for the probable level was significantly higher than that for the possible level (P < 0.05). Scores for confidence in claims after reading labels with and without a visual aid were 5.27 and 4.43, respectively; the score for labeling with a visual aid was significantly higher than for labeling without a visual aid (P < 0.01). Our results provide compelling evidence that providing health claims with qualifying language differentiating levels of scientific evidence can help consumers understand the strength of scientific evidence behind those claims. Moreover, when a visual aid was included, consumers perceived the scientific levels more clearly and had greater confidence in their meanings than when a visual aid was not included. Although this result suggests that consumers react differently to different claim levels, it is not yet clear whether consumers understand the variations in the degree of scientific support.

Korean Learning Assistant System with Automatically Extracted Knowledge (자동 추출된 지식에 기반한 한국어 학습 지원 시스템)

  • Park, Gi-Tae;Lee, Tae-Hoon;Hwang, So-Hyun;Kim, Byeong Man;Lee, Hyun Ah;Shin, Yoon Sik
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.2
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    • pp.91-102
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    • 2012
  • Computer aided language learning has become popular. But the level of automation of constructing a Korean learning assistant system is not so high because a practical language learning system needs large scale knowledge resources, which is very hard to acquire. In this paper, we propose a Korean learning assistant system that utilizes easily obtainable knowledge resources like a corpus, web documents and a lexicon. Our system has three modules - problem solving, pronunciation marker and writing assistant. Automatic problem generator uses a corpus and a lexicon to make problems with one correct answer and three distracters, then verifies their suitability by utilizing frequency information from web documents. We analyze pronunciation rules for a pronunciation marker and recommend appropriate words and sentences in real-time by using data extracted from a corpus. In experiment, we evaluate 400 automatically generated problems, which show 89.9% problem suitability and 64.9% example suitability.

An Automated Approach for Exception Suggestion in Python-based AI Projects (Python 기반 AI 프로젝트에서 예외 제안을 위한 자동화 접근 방식)

  • Kang, Mingu;Kim, Suntae;Ryu, Duksan
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.4
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    • pp.73-79
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    • 2022
  • The Python language widely used in artificial intelligence (AI) projects is an interpreter language, and errors occur at runtime. In order to prevent project failure due to errors, it is necessary to handle exceptions in code that can cause exceptional situations in advance. In particular, in AI projects that require a lot of resources, exceptions that occur after long execution lead to a large waste of resources. However, since exception handling depends on the developer's experience, developers have difficulty determining the appropriate exception to catch. To solve this need, we propose an approach that recommends exceptions to catch to developers during development by learning the existing exception handling statements. The proposed method receives the source code of the try block as input and recommends exceptions to be handled in the except block. We evaluate our approach for a large project consisting of two frameworks. According to our evaluation results, the average AUPRC is 0.92 or higher when performing exception recommendation. The study results show that the proposed method can support the developer's exception handling with exception recommendation performance that outperforms the comparative models.