• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권10호
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• pp.1698-1711
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• 2011

Knowledge is often represented as a set of rules or a semantic network in intelligent systems. Recently, ontology has been widely used to represent semantic knowledge, because it organizes thesaurus and hierarchal information between concepts in a particular domain. However, it is not easy to collect semantic relationships among concepts. Much time and expense are incurred in ontology construction. Collective intelligence can be a good alternative approach to solve these problems. In this paper, we propose a collective intelligence approach of Games With A Purpose (GWAP) to collect various semantic resources, such as words and word-senses. We detail how to construct the semantic information model or ontology from the collected semantic resources, constructing a system named FunWords. FunWords is a Korean lexical-based semantic resource collection tool. Experiments demonstrated the resources were grouped as common nouns, abstract nouns, adjective and neologism. Finally, we analyzed their characteristics, acquiring the semantic relationships noted above. Common nouns, with structural semantic relationships, such as hypernym and hyponym, are highlighted. Abstract nouns, with descriptive and characteristic semantic relationships, such as synonym and antonym are underlined. Adjectives, with such semantic relationships, as description and status, illustration - for example, color and sound - are expressed more. Last, neologism, with the semantic relationships, such as description and characteristics, are emphasized. Weighting the semantic relationships with these characteristics can help reduce time and cost, because it need not consider unnecessary or slightly related factors. This can improve the expressive power, such as readability, concentrating on the weighted characteristics. Our proposal to collect semantic resources from the collective intelligence approach of GWAP (our FunWords) and to weight their semantic relationship can help construct the semantic information model or ontology would be a more effective and expressive alternative.

• 지능정보연구
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• 제19권1호
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• pp.111-123
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• 2013

개념간의 의미적 유사도 및 관계도(Semantic Similarity/Relatedness)를 구하는 연구는 고전적인 연구에서는 데이터 베이스 통합이나 시스템 통합, 그리고 현대의 연구에 있어서는 태그 및 키워드 추출, 연관 단어 추천 등에 걸쳐 다양한 분야에서 활용되어 온 연구이다. 그 연구는 역사가 오래되었을 뿐만 아니라, 경영정보와 컴퓨터 공학, 계산 언어학에 걸쳐 여러 분야에서도 많은 관심을 가져왔던 연구 분야라고 할 수 있다. 그러나, 지금까지의 개념간의 관계도 계산 방식은 미리 만들어진 사전이나 참조할 수 있는 다른 시맨틱 네트워크(Semantic Network)를 이용하여 계산하는 방법이 주를 이루었다. 이러한 접근 방법의 경우, 개념간의 의미적 관계가 변화에 대한 가능성을 고려하지 않는 것이 일반적이다. 하지만, 정보 기술의 발달과 빠른 사회변화는 개념간의 의미관계 등에 변화를 가져오고 있는 것이 현실이다. 사회적으로 일어나는 사건이나, 문화적 변화 등이 개념간의 의미관계를 변화시키는 것을 물론이며, 이러한 변화가 정보 통신 기술의 도움으로 빠르게 공유되고 있다. 이렇게 개념간의 의미 관계가 시간이나 맥락에 따라 빠르게 변화할 수 있는 가능성이 있음에도 불구하고, 기존의 개념간 의미적 유사도 및 관계도에 대한 연구들은 이러한 '의미관계의 변화'에 대한 새로운 문제에 대해 해답을 제시하지 못한 것이 사실이다. 따라서, 본 연구에서는 개념간의 유사도 연구에 있어 지금까지 있어왔던 '정적인 의미간 관계도 패러다임'에서 '동적인 의미간 관계도 패러다임'으로의 전환의 필요성과 그 당위성을 인지 의미론적(Cognitive Semantics)의 관점에서 역설하고자 한다. 인간이 인지하는 개념간의 의미관계가 변화할 수 있는 이론적 근거를 인지 의미론에서 찾아봄으로써, 패러다임 변화의 방향을 구체적으로 제시하였다. 또한 이러한 패러다임의 변화에 맞추어 개념간의 의미적 유사도 및 관계도에 대한 연구가 어떠한 방향으로 나아가야 할지 구체적인 연구 방향을 제시함으로써 관련 연구자들에게 새로운 연구의 가이드라인을 제시하였다.

• 한국CDE학회논문집
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• 제9권3호
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• pp.192-202
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• 2004

This paper introduces an approach to semantic mapping using Product ontology for CPC environment. In CPC environment, it is necessary that the participants in a product life cycle should share the same understanding about the semantic of product terms. For example, they should know that although 'COMPONENT' and 'ITEM' are different word-expressions, they could have the same meaning. In order to handle such terms in the information system, it is desirable that the system automatically recognizes that the terms have the same semantics. Serving this purpose, we described an ontology design methodology using first order logic, knowledge interchange format, and knowledge engineering process. In our approach, we investigated domain knowledge of the Bill Of Material, and then designed Product ontology of it. Based on the ontology, we described syntactic translation, semantic translation, and semantic mapping procedure with an example.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3790-3803
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• 2018

Content-based image retrieval is an approach used to query images based on their semantics. Semantic based retrieval has its application in all fields including medicine, space, computing etc. Semantically generated binary hash codes can improve content-based image retrieval. These semantic labels / binary hash codes can be generated from unlabeled data using convolutional autoencoders. Proposed approach uses semi-supervised deep hashing with semantic learning and binary code generation by minimizing the objective function. Convolutional autoencoders are basis to extract semantic features due to its property of image generation from low level semantic representations. These representations of images are more effective than simple feature extraction and can preserve better semantic information. Proposed activation and loss functions helped to minimize classification error and produce better hash codes. Most widely used datasets have been used for verification of this approach that outperforms the existing methods.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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• pp.189-192
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• 2007

This study proposes a Natural Language Query Framework (NLQF) on the semantic web to support the intelligent deduction at semantic level. A large number of former researches are focused on the knowledge representation on the semantic web. However, to revitalize the intelligent agent (IA)-based automated e-business contract with human customers, there is a need for semantic level approach to the web information. To enable accessing web information at semantic level, this paper discusses the pattern of complex natural language processing at first, and then the semantic web-based natural language inference in e-business environment. The NL-based approach could help the IAs on the web to communicate with customers and other IAs with more natural interface than traditional HTML-based web information. Therefore, our proposed NLQF will be used in semantic web-based intelligent e-business contracts between customers and IAs.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.834-851
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• 2017

The amount of sources of information available on the web using ontologies as support continues to increase and is often heterogeneous and distributed. Ontology alignment is the solution to ensure semantic interoperability. In this paper, we describe a new ontology alignment approach, which consists of combining structure-based and reasoning-based approaches in order to discover new semantic correspondences between entities of different ontologies. We used the biblio test of the benchmark series and anatomy series of the Ontology Alignment Evaluation Initiative (OAEI) 2012 evaluation campaign to evaluate the performance of our approach. We compared our approach successively with LogMap and YAM++ systems. We also analyzed the contribution of our method compared to structural and semantic methods. The results obtained show that our performance provides good performance. Indeed, these results are better than those of the LogMap system in terms of precision, recall, and F-measure. Our approach has also been proven to be more relevant than YAM++ for certain types of ontologies and significantly improves the structure-based and reasoningbased methods.

• 한국언어정보학회지:언어와정보
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• 제2권1호
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• pp.116-156
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• 1998

This paper is an HPSG approach to agreement phenomena involving the Korean honorific expressions. it is shown that the theoretical devices developed by the constraint-based theory of HPSG can be fruitfully used to capture the interactions between syntactic constraints and semantic of pragmatic factors in Korean honorific agreement. The HPSG's semantic feature 'referential index' plays a key rele in discribing the multiple interaction. The constraint-based theory of agreement proves successful in accounting for the phenomenon that may be called 'inconsistent' honorific agreement as well as 'consistent' regular honorific usages. However, this paper acknowledges its limit. Recognizing an important distinction between basic and 'coercive' honorific expressions, it is argued that a systactic-semantic-pragmatic approach such as the present one can only be applied to basic honorific agreement. Being sociolinguistic in nature, coercive honorific agreement is perhaps not amenable to formal linguistic investigation.

• 한국컴퓨터정보학회논문지
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• 제14권10호
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• pp.31-41
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• 2009

시맨틱 웹에서는 메타데이터와 온톨로지를 이용해 정보 리소스의 개념을 정의하고 의미적 연관성을 표현함으로써 지능적인 정보 검색과 자동화된 웹 서비스의 제공이 가능하다. 이러한 시맨틱 웹의 핵심적인 기능을 구현하기 위해서는 온톨로지와 메타데이터와 같은 시맨틱 웹 데이터를 효율적으로 관리하는 것이 무엇보다 중요하다. 따라서 본 논문에서는 시맨틱 웹 데이터의 의미와 구조적인 특성을 고려하여 보다 정확한 질의 결과의 검색과 효율적인 질의 처리를 지원할 수 있는 인덱스 구조를 제안한다. 특히 시맨틱 웹 데이터의 의미와 구조적인 특성을 그대로 표현하기 위해 그래프 데이터 모델을 이용하고 다양한 질의 형태를 그래프 모델 기반의 경로식으로 처리한다. 본 논문에서 제안한 인덱스는 1차적으로 추출 가능한 구조적 경로 정보는 물론 온톨로지를 이용한 추론을 통해 2차적으로 추출 가능한 구조적 경로 정보에 대한 질의를 처리 대상으로 하여 기존연구들과 차별화하며 시맨틱 웹의 개념을 온전히 반영하는 것을 목표로 한다. 또한 실험적 평가를 통해 본 논문에서 제안한 인덱스 구조가 정확성과 효율성 측면에서 우수하며 시맨틱 웹의 다양한 애플리케이션 개발에 적용 가능함을 보인다.

• 한국IT서비스학회지
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• 제10권3호
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• pp.189-201
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• 2011

Feature models are widely used to model commonalities and variabilities among products during software product line development. Feature configurations are generated by selecting the features to be included in individual products. Automated tools to identify errors or inconsistencies in the feature models and configurations are essential to successful software product line engineering. This paper proposes a verification technique and tool based on semantic web technologies such as OWL, SWRL and Protege API. This approach checks the feature model and configuration based on predefined rules and provides information on existence of errors as well as the kinds of those errors. This approach is extensible due to ease of rule modification and may be easily applied to other environments because semantic web technologies can be easily integrated with other programming environments. This paper demonstrates how various semantic web-related technologies can support automatic verification of one kind of software development artifact, the feature model.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2007년도 춘계학술대회
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• pp.79-87
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• 2007

This paper aims to offer a solution based on semantic document classification to improve e-Government utilization and efficiency for people using their own information retrieval system and linguistic expression Generally, semantic document classification method is an approach that classifies documents based on the diverse relationships between keywords in a document without fully describing hierarchial concepts between keywords. Our approach considers the deep meanings within the context of the document and radically enhances the information retrieval performance. Concept Weight Document Classification(CoWDC) method, which goes beyond using exist ing keyword and simple thesaurus/ontology methods by fully considering the concept hierarchy of various concepts is proposed, experimented, and evaluated. With the recognition that in order to verify the superiority of the semantic retrieval technology through test results of the CoWDC and efficiently integrate it into the e-Government, creation of a thesaurus, management of the operating system, expansion of the knowledge base and improvements in search service and accuracy at the national level were needed.