• Title/Summary/Keyword: Word semantics analysis

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Multilingual Word Translation Service based on Word Semantic Analysis (어휘의미분석 기반 다국어 어휘대역 서비스)

  • Ryu, Pum-Mo
    • Journal of Digital Contents Society
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    • v.19 no.1
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    • pp.75-83
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    • 2018
  • Multicultural family members have difficulty in educating their children due to language differences. In order to solve these difficulties, it is necessary to provide smart translation services that enable them easily and quickly access real-life vocabularies. However, the current automatic translation technology is being developed in dominant languages such as English, Chinese, and Japanese. There are also limitations to translating special-purpose terms such as documents of schools and instructions of public institutions. In this study, we propose a real-time automatic word translation service for multicultural family members who understand beginner level Korean. The service automatically analyzes the semantics of each word in the Korean sentences and provides a word-by-word translation. This study includes semantic analysis research for Korean language, building multilingual translation knowledge, and fusion study of language education. We evaluated the word translation service for migrant women from Vietnam and Japan and obtained meaningful evaluation results.

A pilot implementation of Korean in Database Semantics: focusing on numeral-classifier construction (데이터베이스 의미론을 이용한 한국어 구현 시론: 수사-분류사 구조를 중심으로)

  • Choe, Jae-Woong
    • Korean Journal of Cognitive Science
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    • v.18 no.4
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    • pp.457-483
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    • 2007
  • Database Semantics (DBS) attempts to provide a comprehensive and integrated approach to human communication which seeks theory-implementation transparency. Two key components of DBS are Word bank as a data structure and left-Associative Grammar (LAG) as an algorithm. This study aims to provide a pilot implementation of Korean in DBS. First, it is shown how the three separate modules of grammar in DBS, namely, Hear, Think, and Speak, combine to form an integrated system that simulates a cognitive agent by making use of a simple Korean sentence as an example. Second, we provide a detailed analysis of the structure in Korean that is a characteristic of Korean involving numerals, classifiers, and nouns, thereby illustrating how DBS can be applied to Korean. We also discuss an issue raised in the literature concerning a problem that arises when we try to apply the LAG algorithm to the analysis of head-final language like Korean, and then discuss some possible solution to the problem.

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A Simple Syntax for Complex Semantics

  • Lee, Kiyong
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2002.02a
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    • pp.2-27
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    • 2002
  • As pact of a long-ranged project that aims at establishing database-theoretic semantics as a model of computational semantics, this presentation focuses on the development of a syntactic component for processing strings of words or sentences to construct semantic data structures. For design arid modeling purposes, the present treatment will be restricted to the analysis of some problematic constructions of Korean involving semi-free word order, conjunction arid temporal anchoring, and adnominal modification and antecedent binding. The present work heavily relies on Hausser's (1999, 2000) SLIM theory for language that is based on surface compositionality, time-linearity arid two other conditions on natural language processing. Time-linear syntax for natural language has been shown to be conceptually simple and computationally efficient. The associated semantics is complex, however, because it must deal with situated language involving interactive multi-agents. Nevertheless, by processing input word strings in a time-linear mode, the syntax cart incrementally construct the necessary semantic structures for relevant queries and valid inferences. The fragment of Korean syntax will be implemented in Malaga, a C-type implementation language that was enriched for both programming and debugging purposes arid that was particluarly made suitable for implementing in Left-Associative Grammar. This presentation will show how the system of syntactic rules with constraining subrules processes Korean sentences in a step-by-step time-linear manner to incrementally construct semantic data structures that mainly specify relations with their argument, temporal, and binding structures.

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Analyzing the Sentence Structure for Automatic Identification of Metadata Elements based on the Logical Semantic Structure of Research Articles (연구 논문의 의미 구조 기반 메타데이터 항목의 자동 식별 처리를 위한 문장 구조 분석)

  • Song, Min-Sun
    • Journal of the Korean Society for information Management
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    • v.35 no.3
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    • pp.101-121
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    • 2018
  • This study proposes the analysis method in sentence semantics that can be automatically identified and processed as appropriate items in the system according to the composition of the sentences contained in the data corresponding to the logical semantic structure metadata of the research papers. In order to achieve the purpose, the structure of sentences corresponding to 'Research Objectives' and 'Research Outcomes' among the semantic structure metadata was analyzed based on the number of words, the link word types, the role of many-appeared words in sentences, and the end types of a word. As a result of this study, the number of words in the sentences was 38 in 'Research Objectives' and 212 in 'Research Outcomes'. The link word types in 'Research Objectives' were occurred in the order such as Causality, Sequence, Equivalence, In-other-word/Summary relation, and the link word types in 'Research Outcomes' were appeared in the order such as Causality, Equivalence, Sequence, In-other-word/Summary relation. Analysis target words like '역할(Role)', '요인(Factor)' and '관계(Relation)' played a similar role in both purpose and result part, but the role of '연구(Study)' was little different. Finally, the verb endings in sentences were appeared many times such as '~고자', '~였다' in 'Research Objectives', and '~었다', '~있다', '~였다' in 'Research Outcomes'. This study is significant as a fundamental research that can be utilized to automatically identify and input the metadata element reflecting the common logical semantics of research papers in order to support researchers' scholarly sensemaking.

A Comparative Study of Semantic Featueres about 'zheng', 'fa', 'qin', 'xi', 'tao' ('정(征)', '벌(伐)', '침(侵)', '습(襲)', '토(討)'의 의미 특징 비교)

  • Yu, Hyuna
    • Cross-Cultural Studies
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    • v.37
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    • pp.383-400
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    • 2014
  • Synonym means that the conceptual meaning of the word is the same or similar while other meanings or function of language difference may exist. That is two or more identified names correspond with one sense and have the words with minor difference. Words with synonym relation are a set of same meaning but conceptual area or emotional color, language function can be identified. Therefore, the core research of synonym is the difference analysis and in general difference analysis is progress in the three aspects of Meaning, Pragmatic, and Semantic. However, the difference analysis is the most important. In this paper, the set of meaning item of synonym word 'Attack' is 'zheng', 'fa', 'tao', 'qin', 'xi'. We compare the meaning of five verbs and analyze the difference and characteristics.

Question Analysis based on Focus-words for Korean Question-Answering System (한국어 질의 응답 시스템을 위한 초점단어 기반 질의분석)

  • Kim, Won-Nam;Shin, Seung-Eun;Seo, Young-Hoon
    • Proceedings of the Korea Contents Association Conference
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    • 2004.11a
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    • pp.476-482
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    • 2004
  • Question-Answering (QA) system has to analyze user's intention correctly to respond correct answer for user's question., This paper proposes a focus-word-based question analysis approach for Korean QA system to analyze user's intention correctly. focus-word is a clue-word which selects question type. The question type is determined to one in 75 subcategories using semantics of focus-words. the proposed system accomplished 97.18% accuracy for the main category and 95.31% accuracy for the subcategory in the question classification.

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Using Syntax and Shallow Semantic Analysis for Vietnamese Question Generation

  • Phuoc Tran;Duy Khanh Nguyen;Tram Tran;Bay Vo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.10
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    • pp.2718-2731
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    • 2023
  • This paper presents a method of using syntax and shallow semantic analysis for Vietnamese question generation (QG). Specifically, our proposed technique concentrates on investigating both the syntactic and shallow semantic structure of each sentence. The main goal of our method is to generate questions from a single sentence. These generated questions are known as factoid questions which require short, fact-based answers. In general, syntax-based analysis is one of the most popular approaches within the QG field, but it requires linguistic expert knowledge as well as a deep understanding of syntax rules in the Vietnamese language. It is thus considered a high-cost and inefficient solution due to the requirement of significant human effort to achieve qualified syntax rules. To deal with this problem, we collected the syntax rules in Vietnamese from a Vietnamese language textbook. Moreover, we also used different natural language processing (NLP) techniques to analyze Vietnamese shallow syntax and semantics for the QG task. These techniques include: sentence segmentation, word segmentation, part of speech, chunking, dependency parsing, and named entity recognition. We used human evaluation to assess the credibility of our model, which means we manually generated questions from the corpus, and then compared them with the generated questions. The empirical evidence demonstrates that our proposed technique has significant performance, in which the generated questions are very similar to those which are created by humans.

Recent update on reading disability (dyslexia) focused on neurobiology

  • Kim, Sung Koo
    • Clinical and Experimental Pediatrics
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    • v.64 no.10
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    • pp.497-503
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    • 2021
  • Reading disability (dyslexia) refers to an unexpected difficulty with reading for an individual who has the intelligence to be a much better reader. Dyslexia is most commonly caused by a difficulty in phonological processing (the appreciation of the individual sounds of spoken language), which affects the ability of an individual to speak, read, and spell. In this paper, I describe reading disabilities by focusing on their underlying neurobiological mechanisms. Neurobiological studies using functional brain imaging have uncovered the reading pathways, brain regions involved in reading, and neurobiological abnormalities of dyslexia. The reading pathway is in the order of visual analysis, letter recognition, word recognition, meaning (semantics), phonological processing, and speech production. According to functional neuroimaging studies, the important areas of the brain related to reading include the inferior frontal cortex (Broca's area), the midtemporal lobe region, the inferior parieto-temporal area, and the left occipitotemporal region (visual word form area). Interventions for dyslexia can affect reading ability by causing changes in brain function and structure. An accurate diagnosis and timely specialized intervention are important in children with dyslexia. In cases in which national infant development screening tests have been conducted, as in Korea, if language developmental delay and early predictors of dyslexia are detected, careful observation of the progression to dyslexia and early intervention should be made.

Detection of System Abnormal State by Cyber Attack (사이버 공격에 의한 시스템 이상상태 탐지 기법)

  • Yoon, Yeo-jeong;Jung, You-jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.5
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    • pp.1027-1037
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    • 2019
  • Conventional cyber-attack detection solutions are generally based on signature-based or malicious behavior analysis so that have had difficulty in detecting unknown method-based attacks. Since the various information occurring all the time reflects the state of the system, by modeling it in a steady state and detecting an abnormal state, an unknown attack can be detected. Since a variety of system information occurs in a string form, word embedding, ie, techniques for converting strings into vectors preserving their order and semantics, can be used for modeling and detection. Novelty Detection, which is a technique for detecting a small number of abnormal data in a plurality of normal data, can be performed in order to detect an abnormal condition. This paper proposes a method to detect system anomaly by cyber attack using embedding and novelty detection.

Analysis and Computational Processing of Quantifier Floating in Korean (양화사유동과 관련된 한국어의 분석과 전산처리)

  • 이진복;박종철
    • Language and Information
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    • v.7 no.1
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    • pp.1-22
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    • 2003
  • Quantifier floating is one of the much studied phenomena in natural languages where quantifying expressions may appear in places other than their original prenominal one. Its presence is especially prominent in languages such as Korean that allow more or less free word order. We find that, in addition to what is described in the literature, there are other remarkable regularities in the way the language allows quantifiers to “float” with respect to various constructions including coordination, relative clauses, and embedded clauses. These regularities are captured syntactically in a combinatory categorial grammar (CCG) framework for Korean. We also show how to derive semantic representations for Korean quantifier floating in the same CCG framework.

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