• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.369-378
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• 2005

본 논문에서는 유비쿼터스 환경에서 유동 소비자가 서비스의 유동성을 보장받을 수 있는 지능형 여행정보서비스를 제안하고자 한다. 본 시스템은 유비쿼터스 환경에서 여행자가 필요로 하는 정보획득을 돕기 위해 다양한 상품제안, 그 상품들 간의 연계를 통한 맞춤제안을 목적으로 설계되었다 여행정보시스템에 연관된 상품들은 호텔, 비행사, 자동차, 여행지 정보, 음식점 및 Business Trip 등이다. 따라서 여행자의 요구 및 상황의 변화에 맞게 연관상품의 Schedule 맞춤을 위한 지능형 여행 최적정보시스템의 연구가 요구된다. 이를 위해 본 연구에서는 Traveling Service 지원을 위해 첫째 여행자의 요구에 따른 단일상품의 복합상품화(Product bundling)를 위한 방법론을 제안하였다. 둘째, 복합상품을 구성하기 위해 필수적인, 개별정보시스템에 이질적인 형태로 저장되어있는 단일상품에 대한 정보를 공유하기 위해, 여행상품과 온톨로지의 구축이 요구된다. 이에 본 논문에서는 OWL 기반의 온톨로지를 구축하였다. 온톨로지 기반의 여행정보시스템은 향후 시맨틱 웹서비 기반의 지능형 여행정보시스템 구축을 위한 초석으로 활요될 것이다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.184-186
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• 2004

최근에 이르러 온톨로지 (Ontology) 및 시맨틱 웹 (Semantic Web) (1) 에 대한 연구가 활발히 진행됨에 따라 이들을 처리할 수 있는 에이전트 시스템의 중요성 또한 부각되고 있다. 이러한 에이전트 시스템은 규칙(Rule)을 기반으로 하여 해당 조건을 만족시키는 경우에 규칙에 정의된 행동을 실행하도록 설계된다. 하지만 이러한 시스템이 않은 양의 규칙과 조건을 처리하는 경우 특정한 조건에 맞는 규칙을 검사하는 과정에서 많은 오버헤드가 걸리게 된다. 이러한 시스템의 단점을 보완하고자 사용되는 것이 RETE 알고리즘으로서 각 조건과 규칙들을 빠르게 검색할 수 있는 네트워크를 구성하고 특정 조건이 만족되는 경우 이를 창조하는 규칙들의 목록을 즉시 얻어낼 수 있게 된다. 본 논문에서는 JAM 에이전트 시스템에 RETE 알고리즘을 적용시키고 이를 통해 더욱 효율적인 에이전트 시스템을 구성하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.92-94
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• 2012

시맨틱 웹은 인터넷 환경에서 지식을 표현하고 공유하기 위한 표준 기술들의 집합체이며, 온톨로지는 특정 지식 도메인의 용어와 용어 사이의 관계를 정의한 지식 표현체계이다. 본 연구에서는 시소러스를 SKOS 기반 온톨로지로 모델링하여 LOD로 공개하는 실제적 방법을 제시한다. 시소러스의 어휘 용어 체계와 의미 관계를 분석하고, 이 분석 결과를 활용하여 변환 방식을 정의한 후, SKOS 온톨로지를 생성하며, 그 결과를 DataHub에 등록함으로써 LOD에 공개된다. 과학기술 분야의 한 중 일 대역어와 유사어, 관계어 등의 시소러스를 SKOS 온톨로지로 변환한 데이터는 http://thedatahub.org/dataset/steak에서 확인할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.276-279
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• 2010

소프트웨어 제품 라인 개발 패러다임은 관련 제품들 사이의 공통점과 차이점을 이용해 보다 전략적인 재사용을 가능하게 함으로써 소프트웨어 개발 생산성을 높여 주는 개발 방법론이다. 공통점과 차이점을 분석하고 모델링하기 위해 가장 중요한 모델이 특성 모델이다. 특성 모델은 규모가 커짐에 따라 오류를 포함할 가능성이 커지며 이를 검증하기 위한 자동화된 도구가 필요하다. 본 논문에서는 온톨로지를 자바 언어로 구현 가능하게 해주는 Protege API, OWL기반의 시맨틱 웹 규칙 언어인 SWRL, 규칙 추론 엔진인 Pellet Reasoner 등의 기술을 이용한 특성 모델 검증 도구를 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.450-452
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• 2007

최근 주목을 받고 있는 시맨틱 웹의 핵심인 온톨로지는 특정 도메인의 지식들을 정형화하고, 그들 간의 관계를 표현한 것이다. 이러한 온톨로지를 구축하는는 데에 RDF, OWL, DAML+OIL 과 같은 다양한 언어들이 사용되고 있다. 본 논문에서는 RDF 를 이용하여 데스크탑 컴퓨터 조립을 위한 컴퓨터 부품 온톨로지를 구축하고, RDQL 로 온톨로지를 검색하는 방법을 소개한다. 향후 연구는 기존의 단순 매칭을 통한 검색을 포함한, 추론을 거쳐 최적화된 부품 조합을 얻기 위한 연구를 할 것이다.

• The Journal of Society for e-Business Studies
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• v.11 no.3
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• pp.53-71
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• 2006

In order to cope with the rapidly changing product development environment, individual manufacturing enterprises are forced to collaborate with each other through establishing a virtual organization. In collaboration, designated organizations work together for mutual gain based on product data interoperability. However, product data interoperability is not fully facilitated due to semantic inconsistency among product data models of individual enterprises. In order to overcome the semantic inconsistency problem, this paper proposes a reference ontology, Reference Domain Ontology(RDO), and a methodology for product data interoperability with semantic consistency using RDO. RDO describes semantics of product data model and metamodel for all application domains in a virtual organization. Using RDO, application domains in a virtual organization can easily understand the product data models of others. RDO is agile and temporal such that it is created with the formation of a virtual organization, copes with changes of the organization, and disappears with the vanishment of the organization. RDO is built by a hybrid approach of top-down using a upper ontology and bottom-up based on the merging of ontologies of application domains in a virtual organization. With this methodology, every domain in a virtual organization can achieve product data model interoperability without model transformation.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.986-998
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• 2006

There has been an increasing necessity of Semantic Web-based metadata that helps computers efficiently understand and manage an information increased with the growth of Internet. However, it seems inevitable to face some semantically ambiguous information when metadata is generated. Therefore, we need a solution to this problem. This paper proposes a new method for automated metadata generation with the help of a concept of class, in which some ambiguous words imbedded in information such as documents are semantically more related to others, by using probability model of consequent words. We considers ambiguities among defined concepts in ontology and uses the Hidden Markov Model to be aware of part of a named entity. First of all, we constrict a Markov Models a better understanding of the named entity of each class defined in ontology. Next, we generate the appropriate context from a text to understand the meaning of a semantically ambiguous word and solve the problem of ambiguities during generating metadata by searching the optimized the Markov Model corresponding to the sequence of words included in the context. We experiment with seven semantically ambiguous words that are extracted from computer science thesis. The experimental result demonstrates successful performance, the accuracy improved by about 18%, compared with SemTag, which has been known as an effective application for assigning a specific meaning to an ambiguous word based on its context.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.282-296
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• 2010

OWL is an ontology language for the Semantic Web, and suited to modelling the knowledge of a specific domain in the real-world. Ontology also can infer new implicit knowledge from the explicit knowledge. However, the modeled knowledge cannot be complete as the whole of the common-sense of the human cannot be represented totally. Ontology do not concern handling nonmonotonic reasoning to detect incomplete modeling such as the integrity constraints and exceptions. A default rule can handle the exception about a specific class in ontology. Integrity constraint can be clear that restrictions on class define which and how many relationships the instances of that class must hold. In this paper, we propose a practical reasoning system for open and closed-world reasoning that supports a novel hybrid integration of ontology based on open world assumption (OWA) and non-monotonic rule based on closed-world assumption (CWA). The system utilizes a method to solve the problem which occurs when dealing with the incomplete knowledge under the OWA. The method uses the answer set programming (ASP) to find a solution. ASP is a logic-program, which can be seen as the computational embodiment of non-monotonic reasoning, and enables a query based on CWA to knowledge base (KB) of description logic. Our system not only finds practical cases from examples by the Protege, which require non-monotonic reasoning, but also estimates novel reasoning results for the cases based on KB which realizes a transparent integration of rules and ontologies supported by some well-known projects.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.49-63
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• 2008

RDF is the base ontology model which is used in Semantic Web defined by W3C. OWL expands the RDF base model by providing various vocabularies for defining much more ontology relationships. Recently Jain and Farkas have suggested an RDF access control model based on RDF triple. Their research point is to introduce an authorization conflict problem by RDF inference which must be considered in RDF ontology data. Due to the problem, we cannot adopt XML access control model for RDF, although RDF is represented by XML. However, Jain and Farkas did not define the authorization propagation over the RDF upper/lower ontology concepts when an RDF authorization is specified. The reason why the authorization specification should be defined clearly is that finally, the authorizatin conflict is the problem between the authorization propagation in specifying an authorization and the authorization propagation in inferencing authorizations. In this article, first we define an RDF access authorization specification based on RDF triple in detail. Next, based on the definition, we analyze the authoriztion conflict problem by RDF inference in detail. Next, we briefly introduce a method which can quickly find an authorization conflict by using graph labeling techniques. This method is especially related with the subsumption relationship based inference. Finally, we present a comparison analysis with Jain and Farkas' study, and some experimental results showing the efficiency of the suggested conflict detection method.

• Journal of KIISE
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• v.44 no.4
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• pp.383-391
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• 2017

As we enter a new era of Big Data, the amount of semantic data has rapidly increased. In order to derive meaningful information from this large semantic data, studies that utilize the SWRL(Semantic Web Rule Language) are being actively conducted. SWRL rules are based on data extracted from a user's empirical knowledge. However, conventional reasoning systems developed on single machines cannot process large scale data. Similarly, multi-node based reasoning systems have performance degradation problems due to network shuffling. Therefore, this paper overcomes the limitations of existing systems and proposes more efficient distributed inference methods. It also introduces data partitioning strategies to minimize network shuffling. In addition, it describes a method for optimizing the incremental reasoning process through data selection and determining the rule order. In order to evaluate the proposed methods, the experiments were conducted using WiseKB consisting of 200 million triples with 83 user defined rules and the overall reasoning task was completed in 32.7 minutes. Also, the experiment results using LUBM bench datasets showed that our approach could perform reasoning twice as fast as MapReduce based reasoning systems.