• Journal of KIISE:Databases
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• v.41 no.4
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• pp.242-248
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• 2014

With the rapidly growing amount of information represented in RDF format, efficient querying of RDF graph has become a fundamental challenge. SPARQL is one of the most widely used query languages for retrieving information from RDF dataset. SPARQL is not only simple in its syntax but also powerful in representation of graph pattern queries. However, users need to make a lot of efforts to understand the ontology schema of a dataset in order to compose a relevant SPARQL query. In this paper, we propose a graph query formulation and processing scheme based on ontology schema information which can be obtained by summarizing RDF graph. In the context of the proposed querying scheme, a user can interactively formulate the graph queries on the graphic user interface without making efforts to understand the ontology schema and even without learning SPARQL syntax. The graph query formulated by a user is transformed into a set of class paths, which are stored in a relational database and used as the constraint for search space reduction when the relational database executes the graph search operation. By executing the LUBM query 2, 8, and 9 over LUBM (10,0), it is shown that the proposed querying scheme returns the complete result set.

• Journal of the Korean housing association
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• v.18 no.2
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• pp.121-128
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• 2007

The investigation of the apartment housing as a dwelling type has become the most important and popular research subject to understand the housing culture in Korea. In their methods of typological analysis, it is found that most studies represent each unit plan as a simplified architectural drawing. This type of typology, however, has difficulties in processing a large scale of data set because each representation of a plan contain too many informations. To deal with this problem, this study suggests a new graph-theoretical method by which apartment plans can be represented in a more simple and effective way. This new method is also tested against the sample plans from Gangnam-gu area in Seoul to reveal the design logic hidden in plan configuration. Through a series of analyses, it is verified that there exist a design strategy that guides the particular pattern of zoning and allocation of each room in the plan.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.910-912
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• 2005

Maple은 수학적 표현에 가까운 프로그래밍 언어로, 함수, 표현열(sequence), 집합, 리스트, 배열, 테이블, 등의 자료구조를 가지고 있다. 단순히 과학 계산과 관련된 수식처리뿐만 아니라 수식기호와 표현을 해석하여 그 문법과 의미를 파악할 수 있는 기능을 갖추고 있다. 본 연구에서는 Maple을 이용하여 그래프 이론 학습에 사용할 수 있는 white box형 워크시트를 개발하고, 개발된 워크시트를 웹에서 서비스 할 수 있도록 html로 변환하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.357-364
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• 2019

As industrial information disclosure by insider's rate is around 80%, most of relevant researches explain briefly its causes are discontent of salary or human resources system. This paper scrapes texts on Jobplanet, an anonymous company review website and analyzes discontent keyword by 7 related area and their contexts to find out more details on brief causes referred above. After drawing LGG (Local Grammar Graph) by each areas with related dictionary list, this paper shows an example of concordance as a proof and several ways for human resources leakage prevention. Finally, text analysis results are compared with previous researches based on survey with limited questions and answers. This study is meaningful to expand the scope of employee discontent analysis with company review text and provide more specific, granular and honest discontent vocabularies.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.87-102
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• 2024

Digital transformation refers to the process by which a company or organization changes or innovates its existing business model or sales activities using digital technology. This requires the use of various digital technologies - cloud computing, IoT, artificial intelligence, etc. - to strengthen competitiveness in the market, improve customer experience, and discover new businesses. In addition, in order to derive knowledge and insight about the market, customers, and production environment, it is necessary to select the right data, preprocess the data to an analyzable state, and establish the right process for systematic analysis suitable for the purpose. The usefulness of such digital data is determined by the importance of pre-processing and the correct application of exploratory data analysis (EDA), which is useful for information and hypothesis exploration and visualization of knowledge and insights. In this paper, we reexamine the philosophy and basic concepts of EDA and discuss key visualization information, information expression methods based on the grammar of graphics, and the ACCENT principle, which is the final visualization review standard, for effective visualization.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.123-131
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• 2020

Along with the rapid development of artificial intelligence technology, natural language processing, which deals with human language, is also actively studied. In particular, BERT, a language model recently proposed by Google, has been performing well in many areas of natural language processing by providing pre-trained model using a large number of corpus. Although BERT supports multilingual model, we should use the pre-trained model using large amounts of Korean corpus because there are limitations when we apply the original pre-trained BERT model directly to Korean. Also, text contains not only vocabulary, grammar, but contextual meanings such as the relation between the front and the rear, and situation. In the existing natural language processing field, research has been conducted mainly on vocabulary or grammatical meaning. Accurate identification of contextual information embedded in text plays an important role in understanding context. Knowledge graphs, which are linked using the relationship of words, have the advantage of being able to learn context easily from computer. In this paper, we propose a system to extract Korean contextual information using pre-trained BERT model with Korean language corpus and knowledge graph. We build models that can extract person, relationship, emotion, space, and time information that is important in the text and validate the proposed system through experiments.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.313-316
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• 2016

온톨로지란 사물이나 개념의 속성이나 관계를 사람과 컴퓨터 모두 이해할 수 있는 형태로 표현한 모델로 정보검색, 인공지능, 소프트웨어 공학 등의 분야에서 많이 활용된다. 온톨로지에는 다양한 정보가 구조화되어 저장되어 있지만 일반적으로 온톨로지가 제공하는 그래프 형태의 데이터들은 사용자들이 직관적으로 이해하기가 힘들다. 따라서 본 논문에서는 온톨로지의 정보를 문장화하여 한국어 문서를 생성하는 시스템을 제안한다. 제안하는 시스템은 주제와 관련된 트리플을 추출하고 이를 문장정렬, 결합, 생성을 위한 정보가 담긴 템플릿을 생성한 뒤 한국어 문법에 맞게 문장을 생성한다. 또한 기존 연구에서 다루지 않았던 이벤트 온톨로지의 내용을 포함하여 문장을 생성한다. 두 온톨로지로부터 생성된 문장을 연결하여 주제어를 설명하는 하나의 문서를 작성한다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.248-251
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• 2011

본 연구에서는, 웹 문서로부터 특정 상품에 대한 의견 문장을 분석하는 오피니언 마이닝(Opinion Mining) 연구의 일환으로, 특히 함께 공기하는 자질 명사에 따라 그 극성 값이 달라지는 '비결정 오피니언어휘'의 처리를 위해서 도메인을 '맛집'으로 한정하여 공기하는 도메인 키워드의 목록을 결정하고, 이를 부분문법그래프(Local Grammar Graphs) 방법론을 통해서 이들 간의 어휘 통사적 관계를 결정해 주었다.

• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.313-316
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• 2016

온톨로지란 사물이나 개념의 속성이나 관계를 사람과 컴퓨터 모두 이해할 수 있는 형태로 표현한 모델로 정보검색, 인공지능, 소프트웨어 공학 등의 분야에서 많이 활용된다. 온톨로지에는 다양한 정보가 구조화되어 저장되어 있지만 일반적으로 온톨로지가 제공하는 그래프 형태의 데이터들은 사용자들이 직관적으로 이해하기가 힘들다. 따라서 본 논문에서는 온톨로지의 정보를 문장화하여 한국어 문서를 생성하는 시스템을 제안한다. 제안하는 시스템은 주제와 관련된 트리플을 추출하고 이를 문장정렬, 결합, 생성을 위한 정보가 담긴 템플릿을 생성한 뒤 한국어 문법에 맞게 문장을 생성한다. 또한 기존 연구에서 다루지 않았던 이벤트 온톨로지의 내용을 포함하여 문장을 생성한다. 두 온톨로지로부터 생성된 문장을 연결하여 주제어를 설명하는 하나의 문서를 작성한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.33-36
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• 2018

코드리뷰는 소프트웨어의 신뢰성을 향상시키며, 개발 기간을 단축시킨다. 기존의 코드리뷰 도구들은 문법적인 오류는 검출하지만, 논리적인 오류를 찾아내지 못하는 한계가 있다. 본 논문에서는 Git 히스토리를 이용하여 코드 간의 연관성 그래프를 만들고, 이를 이용하여 논리적인 오류를 찾아내는 도구를 구현하였다. 코드상의 논리적 오류를 검출하여 프로그램 개발을 용이하게 하고, 내부에 잠재되어 있는 결함을 예방할 수 있다.