• Title/Summary/Keyword: Linguistic processing

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Development of Fuzzy-Statistical Control Chart for Processing Uncertain Process Information (불명확한 공정정보 처리를 위한 퍼지-통계적 관리도의 개발)

  • 김경환;하성도
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.2
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    • pp.75-80
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    • 1998
  • Process information is known to have the continuous distribution in many manufacturing processes. Generalized p-chart has been developed for controlling processes by classifying the information characteristics into several groups. But it is improper to describe continuous processes with the classified process informal ion, which is based on the classical set concept. Fuzzy control chart, has been developed for the control of linguistic data, but it is also based on the dichotomous notion of classical set theory. In this paper, fuzzy sampling method is studied in order to process the uncertain data properly. The method is incorporated with the fuzzy control chart. Statistical characteristics of the fuzzy representative value are utilized to device the fuzzy-statistical control chart. The fuzzy-statistical control chart is compared with the generalized p-chart and both the sensitivity to the process information distribution change pared robustiness against the noise on the process information of the fuzzy-statistical control chart are shown to be superior.

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Neuro controller of the robot manipulator using fuzzy logic (퍼지 논리를 이용한 로보트 매니퓰레이터의 신경 제어기)

  • 김종수;이홍기;전홍태
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.866-871
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    • 1991
  • The multi-layer neural network possesses the desirable characteristics of parallel distributed processing and learning capacity, by which the uncertain variation of the parameters in the dynamically complex system can be handled adoptively. However the error back propagation algorithm that has been utilized popularly in the learning procedure of the mulfi-Jayer neural network has the significant limitations in the real application because of its slow convergence speed. In this paper, an approach to improve the convergence speed is proposed using the fuzzy logic that can effectively handle the uncertain and fuzzy informations by linguistic level. The effectiveness of the proposed algorithm is demonstrated by computer simulation of PUMA 560 robot manipulator.

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A Computational Model for Lexical Acquisition in Korean (한국어 어휘습득의 계산주의적 모델)

  • Yo, Won-Hee;Park, Ki-Nam;Lyu, Ki-Gon;Lim, Heui-Seok;Nam, Ki-Chun
    • Proceedings of the KSPS conference
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    • 2007.05a
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    • pp.135-137
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    • 2007
  • This study has experimented and materialized a computational lexical processing model which hybridizes full model and decomposition model as applying lexical acquisition, one of early stages of human lexical processes, to Korean. As the result of the study, we could simulate the lexical acquisition process of linguistic input through experiments and studying, and suggest a theoretical foundation for the order of acquitting certain grammatical categories. Also, the model of this study has shown proofs with which we can infer the type of the mental lexicon of the human cerebrum through fu1l-list dictionary and decomposition dictionary which were automatically produced in the study.

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영한자동번역에서의 두단계 영어 전산문법

  • 최승권
    • Language and Information
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    • v.4 no.1
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    • pp.97-109
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    • 2000
  • Application systems of natural language processing such as machine translation system must deal with actual texts including the full range of linguistic phenomena. But it seems to be impossible that the existing grammar covers completely such actual texts because they include disruptive factors such as long sentences, unexpected sentence patterns and erroneous input to obstruct well-formed analysis of a sentence. In order to solve analysis failure due to the disruptive factors or incorrect selection of correct parse tree among forest parse trees, this paper proposes two-level computational grammar which consists of a constraint-based grammar and an error-tolerant grammar. The constraint-based computational grammar is the grammar that gives us the well-formed analysis of English texts. The error-tolerant computational grammar is the grammar that reconstructs a comprehensible whole sentence structure with partially successful parse trees within failed parsing results.

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Morphological Ambiguity Reduction Using Linguistic Knowledge (언어지식을 이용한 형태소 해석의 모호성 축소)

  • Kim, Jae-Hoon;Kim, Gil-Chang
    • Annual Conference on Human and Language Technology
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    • 1996.10a
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    • pp.231-234
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    • 1996
  • 가능한 모든 형태소 해석을 찾아내는 한국어 형태소 해석기들은 필요 이상으로 많은 수의 형태소 해석 결과를 생성하기 때문에, 자연언어 처리 시스템의 상위 과정, 즉 구문해석, 의미해석 등에 큰 도움이 되지 못하고 있는 실정이다. 이러한 문제점을 해결하기 위해서, 본 논문에서는 어휘화된 배열규칙과 형태적 포섭관계와 같은 언어지식을 이용해서, 형태소 해석의 모호성 축소 방법을 제안하고자 한다. 실험 및 평가를 위해서 KAIST 말뭉치를 이용하였으며, 평가의 기준을 설정하기 위해서 품사 쌍의 접속정보를 배열규칙으로 하는 한국어 형태소 해석기를 사용하였다. 어휘화된 배열규칙과 형태적 포섭관계를 이용했을 경우, 각각 54%와 40.4%의 형태소 해석의 모호성 감소율을 보였으며, 이들 두 방법을 동시에 적용했을 경우, 67.5%의 형태소 해석의 모호성 감소율을 보였다.

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A Comparison of the Performances of Confrontation Naming Test and Verbal Fluency Task in Patients with Prodromal Alzheimer's Disease and Mild Alzheimer's Disease (노인성 알츠하이머병 위험군과 초기 알츠하이머병 환자의 이름대기와 구어유창성 능력의 비교)

  • Choi, Hyun-Joo
    • Speech Sciences
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    • v.15 no.2
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    • pp.111-118
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    • 2008
  • We identified the characteristic impairmants of linguistic semantic memory in patients with prodromal Alzheimer's disease(AD) and mild AD. To elucidate the earliest changes of semantic language function in subjects with AD, performances on confrontation naming test and verbal fluency task were compared among patients with AD patients (n=20), mild AD patients (n=27) and healthy elderly controls (n=20). Tasks in this study included the confrontation naming test of Test of Lexical Processing in Aphasia(TLPA/Japanese) and one-minute verbal fluency task (semantic/ phonetic categories). The results were as follows: 1) Performances of the prodromal AD group showed the comparable to those of the control group on the confrontation naming test, 2) In the semantic/phonetic verbal fluency tasks, the performances of the control group were better than those of the prodromal AD and mild AD groups, but no significant differences were shown between the prodromal AD and the mild AD group.

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Semi-Automatic Annotation Tool to Build Large Dependency Tree-Tagged Corpus

  • Park, Eun-Jin;Kim, Jae-Hoon;Kim, Chang-Hyun;Kim, Young-Kill
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2007.11a
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    • pp.385-393
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    • 2007
  • Corpora annotated with lots of linguistic information are required to develop robust and statistical natural language processing systems. Building such corpora, however, is an expensive, labor-intensive, and time-consuming work. To help the work, we design and implement an annotation tool for establishing a Korean dependency tree-tagged corpus. Compared with other annotation tools, our tool is characterized by the following features: independence of applications, localization of errors, powerful error checking, instant annotated information sharing, user-friendly. Using our tool, we have annotated 100,904 Korean sentences with dependency structures. The number of annotators is 33, the average annotation time is about 4 minutes per sentence, and the total period of the annotation is 5 months. We are confident that we can have accurate and consistent annotations as well as reduced labor and time.

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ADAPTIVE, REAL-TIME TRAFFIC CONTROL MANAGEMENT

  • Nakamiti, G.;Freitas, R.
    • International Journal of Automotive Technology
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    • v.3 no.3
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    • pp.89-94
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    • 2002
  • This paper presents an architecture for distributed control systems and its underlying methodological framework. Ideas and concepts of distributed systems, artificial intelligence, and soft computing are merged into a unique architecture to provide cooperation, flexibility, and adaptability required by knowledge processing in intelligent control systems. The distinguished features of the architecture include a local problem solving capability to handle the specific requirements of each part of the system, an evolutionary case-based mechanism to improve performance and optimize controls, the use of linguistic variables as means for information aggregation, and fuzzy set theory to provide local control. A distributed traffic control system application is discussed to provide the details of the architecture, and to emphasize its usefulness. The performance of the distributed control system is compared with conventional control approaches under a variety of traffic situations.

The Adaptive SPAM Mail Detection System using Clustering based on Text Mining

  • Hong, Sung-Sam;Kong, Jong-Hwan;Han, Myung-Mook
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.6
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    • pp.2186-2196
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    • 2014
  • Spam mail is one of the most general mail dysfunctions, which may cause psychological damage to internet users. As internet usage increases, the amount of spam mail has also gradually increased. Indiscriminate sending, in particular, occurs when spam mail is sent using smart phones or tablets connected to wireless networks. Spam mail consists of approximately 68% of mail traffic; however, it is believed that the true percentage of spam mail is at a much more severe level. In order to analyze and detect spam mail, we introduce a technique based on spam mail characteristics and text mining; in particular, spam mail is detected by extracting the linguistic analysis and language processing. Existing spam mail is analyzed, and hidden spam signatures are extracted using text clustering. Our proposed method utilizes a text mining system to improve the detection and error detection rates for existing spam mail and to respond to new spam mail types.

GNI Corpus Version 1.0: Annotated Full-Text Corpus of Genomics & Informatics to Support Biomedical Information Extraction

  • Oh, So-Yeon;Kim, Ji-Hyeon;Kim, Seo-Jin;Nam, Hee-Jo;Park, Hyun-Seok
    • Genomics & Informatics
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    • v.16 no.3
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    • pp.75-77
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    • 2018
  • Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Text corpus for this journal annotated with various levels of linguistic information would be a valuable resource as the process of information extraction requires syntactic, semantic, and higher levels of natural language processing. In this study, we publish our new corpus called GNI Corpus version 1.0, extracted and annotated from full texts of Genomics & Informatics, with NLTK (Natural Language ToolKit)-based text mining script. The preliminary version of the corpus could be used as a training and testing set of a system that serves a variety of functions for future biomedical text mining.