• The Journal of the Korea Contents Association
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• v.6 no.6
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• pp.42-49
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• 2006

XML used rapid method of meta language representation in internet for information transmission. In addition to XML Schema used frequency specification to variety data type. This thesis designed to Simple Type meta model of XML schema using UML. But because structure of XML schema complicate and suppose variety data type we can recognize many difficult matter to user's apprehension and application of model properties that appeared UML. To way out of this matter this study could specified clearly to structured expression in XML schema meta model that is applied OCL specification and together, come up with method of detailed design to parse tree and token generation for lexical and symmentics analysis in compile step on this study foundation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.37-47
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• 2011

In the recent years, malicious codes called malware are having shown significant increase due to the code obfuscation to evade detection mechanisms. When the code obfuscation technique is applied to malwares, they can change their instruction sequence and also even their signature. These malwares which have same functionality and different appearance are able to evade signature-based AV products. Thus, AV venders paid large amount of cost to analyze and classify malware for generating the new signature. In this paper, we propose a novel approach for detecting metamorphic malwares. The proposed mechanism first converts malware's API call sequences to call graph through dynamic analysis. After that, the callgraph is converted to semantic signature using 128 abstract nodes. Finally, we extract all subgraphs and analyze how similar two malware's behaviors are through subgraph similarity. To validate proposed mechanism, we use 273 real-world malwares include obfuscated malware and analyze 10,100 comparison results. In the evaluation, all metamorphic malwares are classified correctly, and similar module behaviors among different malwares are also discovered.

• Journal of KIISE
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• v.42 no.3
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• pp.361-366
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• 2015

Gap parsing is an algorithm for parsing incomplete input strings which include some gaps. Gap parsing is different from conventional parsing, and as known results, one-gap parsing algorithms for arbitrary context-free grammar and LL(1) grammar have $O(n^3)$ and $O(n^2)$ time complexity, respectively. This paper presents a one-gap parsing algorithm for extended PLR(1) grammars. Extended PLR(1) grammars are the class of grammars smaller than LR(1) but much larger than LL(1). The one-gap parsing algorithm of the grammar class is shown to have the time complexity of $O(n^2)$, which is equal to the complexity of one-gap parsing algorithms for LL(1) grammars.

• Annual Conference on Human and Language Technology
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• 1998.10c
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• pp.222-229
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• 1998

본 논문에서는 X-바 이론을 한국어에 적용하여 서로 다른 범주들간의 구조적 일반성을 파악하고, 한국어에 가능한 규칙만을 허용하여 불가능한 규칙을 배제시킬 수 있는 틀을 제시하고자 한다. 한국어가 비중심어간 어순이 자유롭고 기능어가 발달했다는 점을 고려하여, 중심어와 보충어 관계 중심의 기존 X-바 이론을 통사적 파생과 의미적 파생, 수식 및 하위범주의 관계를 중심으로 변형한다. 또한, 한국어의 빈번한 생략현상과 부분 자유 어순에 효과적으로 대응할 수 있도록 이진결합 중심의 CNF(Chomsky Normal Form)를 따른다. 제안하는 자질기반의 한국어 구구조 문법은 직관적이고 간단하면서도 대부분의 문장을 처리할 수 있을 만큼 표현력이 뛰어나다는 장점이 있다. 신문기사에서 454문장을 추출하여 실험한 결과, 약 97%의 문장에 대해 올바른 구문 분석 결과를 생성할 수 있음을 보였다.

• Annual Conference on Human and Language Technology
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• 2007.10a
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• pp.233-240
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• 2007

온톨로지 구축에서 클래스간 관계 설정은 중요한 부분이다. 본 논문에서는 클래스간 상 하위 관계 외의 관계 설정을 위한 클래스간 관계 자동 정의를 목적으로 의존구문분석의 (주어, 용언) (목적어, 용언) 쌍들을 추출하고, 이렇게 추출된 데이터를 이용하여 용언들을 클러스터링 하는 방법을 제안한다. 도메인 전문 코퍼스 데이터 희귀성 문제를 해결하고자, 웹검색을 결합한 방식을 선택하여 도메인 온톨로지 구축 클래스간 관계 자동 설정에 대한 방법론을 제시한다.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.6
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• pp.61-74
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• 2023

The concept of "green infrastructure" emphasizes the close relationship between natural and urban social systems, thereby providing services that protect the ecological environment and improve the quality of human life. The Green View Index(GVI) is an important indicator for measuring the supply of urban green space and contains more 3D spatial elements concerning the green space ratio. This study focused on an area within the Third Ring Road in the city of Chengdu, Sichuan Province, China. The purposes of this study were three-fold. First, this study analyzed the spatial distribution characteristics of the GVI in urban streets and its correlation with the urban park green space system using Street View image data. Second to analyze the characteristics of low GVI streets were analyzed. Third, to analyze the connectivity between road traffic and street GVI using space syntax were analyzed. This study found that the Street GVI was higher in the southwestern part of the study area than in the northeastern part. The spatial distribution of the street GVI correlated with urban park green space. Second, the street areas with low GVI are mainly concentrated in areas with dense commercial facilities, areas with new construction, areas around elevated roads, roads below Class 4, and crossroads areas. Third, the high integration and low GVI areas were mainly concentrated within the First Ring Road in the city as judged by the concentration of vehicles and population. This study provides base material for future programs to improve the GVI of streets in Chengdu, Sichuan Province.

• Korean Journal of Cognitive Science
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• v.12 no.3
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• pp.1-18
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• 2001

The goal of this paper is the pedagogical application of a Korean Spell/Grammar Checker to the web-based language learning system for Korean writing. To maximize the efficient instruction of our learning system \\`Urimal Baeumteo\\` we have to improve our Korean Spell/Grammar Checker. Today the NLP system\\`s performance defends on its semantic processing capability. In our Korean Spell/Grammar Checker. the tasks accomplished in the semantic level are: the detection and correction of misused derived and compound nouns in a Korean spell-checking device and the detection and correction of syntactic and semantic errors in a Korean grammars-checking device. We describe a common approach to the partial parsing using collocation rules based on the dependency grammar. To provide more detailed semantic rules. we classified nouns according to their concepts. and subcategorized verbs referring to their syntactic and semantic features. Improving a Korean Spell/Gl-Grammar Checker makes our learning system active and intelligent in a web-based environment. We acknowledge the flaws in our system: the classification of nouns based on their meanings and concepts is a time consuming task. the analytic unit of this study is principally limited to the phrases in a sentence therefore the accurate parsing of embedded sentences remains a difficult problem to solve. Concerning the web-based language learning system. it is critically important to consider its interface design and structure of its contents.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.449-458
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• 2010

As occasion demands to obtain efficient information from many documents and reviews on the Internet in many kinds of fields, automatic classification of opinion or thought is required. These automatic classification is called sentiment classification, which can be divided into three steps, such as subjective expression classification to extract subjective sentences from documents, sentiment classification to classify whether the polarity of documents is positive or negative, and strength classification to classify whether the documents have weak polarity or strong polarity. The latest studies in Opinion Mining have used N-gram words, lexical phrase pattern, and syntactic phrase pattern, etc. They have not used single word as feature for classification. Especially, patterns have been used frequently as feature because they are more flexible than N-gram words and are also more deterministic than single word. Theses studies are mainly concerned with English, other studies using patterns for Korean are still at an early stage. Although Korean has a slight difference in the meaning between predicates by the change of endings, which is 'Eomi' in Korean, of declinable words, the earlier studies about Korean opinion classification removed endings from predicates only to extract stems. Finally, this study introduces the earlier studies and methods using pattern for English, uses extracted sentimental patterns from Korean documents, and classifies polarities of these documents. In this paper, it also analyses the influence of the change of endings on performances of opinion classification.

• The Journal of Korean Association of Computer Education
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• v.7 no.6
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• pp.1-12
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• 2004

Current computer education is difficult to educate basic concepts and principals of the computer science because the 7th curriculum of computer education is focused on the application of software. According to the ACM K-12 report about the computer science education model, current computer education is taking the wrong way and we should put the highly priority on the education of the fundamentals through programming languages for a better computer education oriented to the computer science. This paper introduces a new object-oriented educational programming language "Dolittle". The design principals of Dolittle are simple syntax of Korean, incremental programming, text based programming, aliasing of function, and object-oriented programming. Being applied to middle school classes, we can confirm that Dolittle is easy to learn, and gives rise to high interest and keeps interest through a course, and also is of great practical use in class for programming novice.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.791-798
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• 2002

In this thesis. we present a new method for inducing a probabilistic dependency grammar (PDG) from text corpus. As words in Korean are composed of a set of more basic morphemes, there exist various dependency relations in a word. So, if the induction process does not take into account of these in-word dependency relations, the accuracy of the resulting grammar nay be poor. In comparison with previous PDG induction methods. the main difference of the proposed method lies in the fact that the method takes into account in-word dependency relations as well as inter-word dependency relations. To access the performance of the proposed method, we conducted an experiment using a manually-tagged corpus of 25,000 sentences which is complied by Korean Advanced Institute of Science and Technology (KAIST). The grammar induction produced 2,349 dependency rules. The parser with these dependency rules shoved 69.77% accuracy in terms of the number of correct dependency relations relative to the total number dependency relations for best-1 parse trees of sample sentences. The result shows that taking into account in-word dependency relations in the course of grammar induction results in a more accurate dependency grammar.