• Title/Summary/Keyword: machine-readable

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Xenie: Integration of Human 'gene to function'information in human readable & machine usable way

  • Ahn, Tae-Jin
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2000.11a
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    • pp.53-55
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    • 2000
  • Xenie is the JAVA application software that integrates and represents 'gene to function'information of human gene. Xenie extracts data from several heterogeneous molecular biology databases and provides integrated information in human readable and machine usable way. We defined 7 semantic frame classes (Gene, Transcript, Polypeptide, Protein_complex, Isotype, Functional_object, and Cell) as a common schema for storing and integrating gene to function information and relationship. Each of 7 semantic frame classes has data fields that are supposed to store biological data like gene symbol, disease information, cofactors, and inhibitors, etc. By using these semantic classes, Xenie can show how many transcripts and polypeptide has been known and what the function of gene products is in General. In detail, Xenie provides functional information of given human gene in the fields of semantic objects that are storing integrated data from several databases (Brenda, GDB, Genecards, HGMD, HUGO, LocusLink, OMIM, PIR, and SWISS-PROT). Although Xenie provide fully readable form of XML document for human researchers, the main goal of Xenie system is providing integrated data for other bioinformatic application softwares. Technically, Xenie provides two kinds of output format. One is JAVA persistent object, the other is XML document, both of them have been known as the most favorite solution for data exchange. Additionally, UML designs of Xenie and DTD for 7 semantic frame classes are available for easy data binding to other bioinformatic application systems. Hopefully, Xenie's output can provide more detailed and integrated information in several bioinformatic systems like Gene chip, 2D gel, biopathway related systems. Furthermore, through data integration, Xenie can also make a way for other bioiformatic systems to ask 'function based query'that was originally impossible to be answered because of separatly stored data in heterogeneous databases.

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The Logical Structure for Standardization of printed Dictionary (표준화를 위한 일반 사전의 논리 구조)

  • Choi, Byung-Jin;Lee, Jae-Sung;Lee, Woon-Jae;Choi, Key-Sun
    • Annual Conference on Human and Language Technology
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    • 1996.10a
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    • pp.415-423
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    • 1996
  • 컴퓨터의 발달과 더불어 최근 자연언어 처리 분야의 일부에서는 일반 문서들(human-readable text)을 전자 문서(machine-readable text)화 하려는 노력이 이루어지고 있다. 이러한 연구 중 대표적인 것으로 사전을 전자문서화된 형태로 바꾸는 작업을 들 수 있는데, 외국에서는 이미 10여년 전부터 이에 관한 연구가 꾸준히 진행되어 결실을 맺고 있다. 이에 반해 우리나라에는 아직 이에 견줄만한, 나아가 표준화할 만한 전자사전이 아직 개발되어 있지 않은 상황이다. 따라서 본고에서는, 일반 사전을 전자사전화 하기 위한 정형화된 논리적 구조를 검토해 보기로 한다.

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The Construction of Korean-to-English Verb Dictionary for Phrase-to-Phrase Translations (구절 변환을 위한 한영 동사 사전 구성)

  • Ok, Cheol-Young;Kim, Yung-Taek
    • Annual Conference on Human and Language Technology
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    • 1991.10a
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    • pp.44-57
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    • 1991
  • In the transfer machine translation, transfer dictionary decides the complexity of the transfer phase and the quality of translation according to the types and precision of informations supplied in the dictionary. Using the phrasal level translated informations within the human readable dictionary, human being translates a source sentence correctly and naturally. In this paper, we propose the verb transfer dictionary in which the various informations are constructed so the machine readable format that the Korean-to-English machine translation system can utilize them. In the proposed dictionary, we first provide the criterions by which an appropriate target verb is selected in phrase-to-phrase translations without an additional semantic analysis in transfer phase. Second, we provide the concrete sentence structure of a target verb so that we can resolve the expressive gaps between two languages and reduce the complexity of the various structure transfer in word-to-word translation.

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Learning Rules for Identifying Hypernyms in Machine Readable Dictionaries (기계가독형사전에서 상위어 판별을 위한 규칙 학습)

  • Choi Seon-Hwa;Park Hyuk-Ro
    • The KIPS Transactions:PartB
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    • v.13B no.2 s.105
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    • pp.171-178
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    • 2006
  • Most approaches for extracting hypernyms of a noun from its definitions in an MRD rely on lexical patterns compiled by human experts. Not only these approaches require high cost for compiling lexical patterns but also it is very difficult for human experts to compile a set of lexical patterns with a broad-coverage because in natural languages there are various expressions which represent same concept. To alleviate these problems, this paper proposes a new method for extracting hypernyms of a noun from its definitions in an MRD. In proposed approach, we use only syntactic (part-of-speech) patterns instead of lexical patterns in identifying hypernyms to reduce the number of patterns with keeping their coverage broad. Our experiment has shown that the classification accuracy of the proposed method is 92.37% which is significantly much better than that of previous approaches.

The Automatic Extraction of Hypernyms and the Development of WordNet Prototype for Korean Nouns using Korean MRD (Machine Readable Dictionary) (국어사전을 이용한 한국어 명사에 대한 상위어 자동 추출 및 WordNet의 프로토타입 개발)

  • Kim, Min-Soo;Kim, Tae-Yeon;Noh, Bong-Nam
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.6
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    • pp.847-856
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    • 1995
  • When a human recognizes nouns in a sentence, s/he associates them with the hyper concepts of onus. For computer to simulate the human's word recognition, it should build the knowledge base (WordNet)for the hyper concepts of words. Until now, works for the WordNet haven't been performed in Korea, because they need lots of human efforts and time. But, as the power of computer is radically improved and common MRD becomes available, it is more feasible to automatically construct the WordNet. This paper proposes the method that automatically builds the WordNet of Korean nouns by using the descripti on of onus in Korean MRD, and it proposes the rules for extracting the hyper concepts (hypernyms)by analyzing structrual characteristics of Korean. The rules effect such characteristics as a headword lies on the rear part of sentences and the descriptive sentences of nouns have special structure. In addition, the WordNet prototype of Korean Nouns is developed, which is made by combining the hypernyms produced by the rules mentioned above. It extracts the hypernyms of about 2,500 sample words, and the result shows that about 92per cents of hypernyms are correct.

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A Study on Conversion of KORMARC(Korean Machine Readable Cataloging) into XML (한국문헌 자동화목록형식 (KORMARC)의 XML 변환에 관한 연구)

  • 김수형;이경현
    • Proceedings of the Korea Multimedia Society Conference
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    • 2001.06a
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    • pp.49-53
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    • 2001
  • 인터넷에서의 정보자원의 증가에 따라 정보자원관리 기법의 관심이 높아지고 있는 가운데 기존의 HTML과 SGML의 단점을 보완한 구조화된 포맷인 XML의 응용에 대한 연구가 활발해지고 있다. 본 논문에서는 전통적인 도서관에서 서지레코드로 널리 사용되고 있는 구조화된 포맷인 MARC을 대상으로 현황과 문제점을 살펴보고, MARC을 XML로 변환하는 데 따른 기대효과를 고찰한다. 또한, 우리나라 MARC 포맷인 KORMARC을 XML로 변환하기 위하여 KORMARC에 대한 DTD를 설계한다.

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Ontology Language based on Topic Maps for Semantic Web Service (시맨틱 웹 서비스를 위한 Topic Maps 기반의 온톨로지 언어)

  • 황윤영;유정연;유소연;이규철
    • Proceedings of the CALSEC Conference
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    • 2003.09a
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    • pp.191-196
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    • 2003
  • The Semantic web service is able to intelligently discover, execute, composite and monitor the Web Service. It constructs the ontology on Web Service and describes the Semantic Markup in the machine-readable form. The currently developing technologies of the Semantic Web Service discovery are DAML-S matchmaker in Carnegie Mellon University, Process Handbook in MIT and etc. In this paper, we propose the ontology language based on Topic Maps that supports the benefits and solves the problems of the Semantic Web Service discovery technologies .

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빅데이터 이용 확산을 위한 ODI 기반 데이터 액세스 프레임워크

  • Kim, Hwa-Jong
    • Information and Communications Magazine
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    • v.31 no.11
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    • pp.67-71
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    • 2014
  • 최근 사회 각 분야에서 빅데이터를 분석하여 새로운 가치를 찾아내려는 시도가 급속히 증가하고 있다. 그러나 빅데이터를 분석하여 소기의 성과를 얻으려면 한 기관이나 기업이 자체로 보유하고 있는 데이터 뿐 아니라 외부에 있는 가치 있는 데이터가 필수적으로 필요한 경우가 대부분이다. 현재 빅데이터 이용에서 가장 어려운 것은 대용량 데이터를 다루는 하드웨어나 분석 소프트웨어 도입이 아니라 핵심적으로 필요한 외부 빅데이터를 어떻게 확보할 것인가이다. 본 고에서는 빅데이터를 효과적으로 공유하고 활용하기 위한 방안으로 오픈 데이터 인터페이스(ODI)를 제안한다. ODI를 사용함으로써 프로그램이 직접 읽을 수 있는(machine readable) 데이터 공유가 확대되고, 데이터 매쉬업이 쉬워지며, 개인의 데이터 가공 능력을 거래할 수 있는 생태계 구현이 가능해질 것이다.