• Journal of KIISE:Databases
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• v.37 no.2
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• pp.92-103
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• 2010

The Web Ontology Language (OWL) has become the W3C recommendation for publishing and sharing ontologies on the Semantic Web. To derive hidden information from OWL data, a number of OWL reasoners have been proposed. Since OWL reasoners are memory-based, they cannot handle large-sized OWL data. To overcome the scalability problem, RDBMS-based systems have been proposed. These systems store OWL data into a database and perform reasoning by incorporating the use of a database. However, they do not consider complete reasoning on all types of properties defined in OWL and the database schemas they use are ineffective for reasoning. In addition, they do not manage updates to the OWL data which can occur frequently in real applications. In this paper, we compare various database schemas used by RDBMS-based systems and propose an improved schema for efficient reasoning. Also, to support reasoning for all the types of properties defined in OWL, we propose a complete and efficient reasoning algorithm. Furthermore, we suggest efficient approaches to managing the updates that may occur on OWL data. Experimental results show that our schema has improved performance in OWL data storage and reasoning, and that our approaches to managing updates to OWL data are more efficient than the existing approaches.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1585-1600
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• 2009

The goal of Semantic Web is to provide efficient and effective semantic search and web services based on the machine-processable semantic information of web resources. Therefore, the process of creating and adding computer-understandable metadata for a variety of web contents, namely, semantic annotation is one of the fundamental technologies for the semantic web. Recently, in order to manage annotation metadata, direct approach for embedding metadata into the document is mainly used in semantic annotation. However, many semantic annotation tools for web documents have been mainly worked with HTML documents, and most of these tools do not support semantic search functionalities using the metadata. In this paper, based on these problems and previous works, we propose the Ontology-based Semantic Annotation tool(OSA) to efficiently support semantic annotation for web documents(such as HTML, PDF). We define a semantic annotation model that represents ontological-semantic information by using RDFS(RDF Schema). Based on XMP(eXtensible Metadata Platform) standard, the model is encoded directly into the document. By using OSA with XMP, user can perform semantic annotation on web documents which are able to keep compatibility for managing annotation metadata. Eventually, the integrated semantic annotation metadata can be used effectively in semantic search for a variety of web contents.

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.247-260
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• 2003

To share and standardize information, especially in the database environments, MDR (Metadata Registry) can be used to integrate various heterogeneous databases within a particular domain. But due to the discrepancies of data element representation between organizations, global information integration is not so easy. And users who are searching integrated information on the Web have limitation to obtain schema information for the underlying source databases. To solve those problems, in this paper, we present a 3-layered Information Integration System (LI2S) based on MDRs and Ontology. The purpose of proposed architecture is to define information integration model, which combine both of the nature of MDRs standard specification and functionality of ontology for the concept and relation. Adopting agent technology to the proposed model plays a key role to support the hierarchical and independent information integration architecture. Ontology is used as for a role of semantic network from which it extracts concept from the user query and the establishment of relationship between MDRs for the data element. (MDR and Knowledge Base are used as for the solution of discrepancies of data element representation between MDRs. Based on this architectural concept, LI2S was designed and implemented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1701-1707
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• 2010

This study is intended for implementing the system environment that can help integrate and retrieve various types of data in real-time by providing semantic interoperability among distributed heterogeneous information systems. The semantic interoperability is made possible by providing a TMDR(Topicmaps Metadata Registry), a set of ontologies. TMDR, which has been made by combining MDR(MetaData Registry) and TopicMaps and storing them in the database, is able to generate distributed query and provide efficient knowledge. MDR is a metadata management technique for distributed data management. TopicMaps is an ontology representation technique that takes into consideration the hierarchy and association for accessing knowledge data. We have created TMDR, a kind of ontology, that is fit for any system and able to detect and resolve semantic conflicts on the level of data and schema. With this system we propose a query-processing technique to integrate and access heterogeneous information sources. Unlike existing retrieval methods this makes possible efficient retrieval and reasoning by providing association focusing on subjects.

• Journal of KIISE
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• v.45 no.3
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• pp.224-233
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• 2018

Recently, there are many of studies on SWRL reasoning engine based on user-defined rules in a distributed environment using a large-scale ontology. Unlike the schema based axiom rules, efficient inference orders cannot be defined in SWRL rules. There is also a large volumet of network shuffled data produced by unnecessary iterative processes. To solve these problems, in this study, we propose a method that uses Map-Reduce algorithm and distributed in-memory framework to deduce multiple rules simultaneously and minimizes the volume data shuffling occurring between distributed machines in the cluster. For the experiment, we use WiseKB ontology composed of 200 million triples and 36 user-defined rules. We found that the proposed reasoner makes inferences in 16 minutes and is 2.7 times faster than previous reasoning systems that used LUBM benchmark dataset.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.434-436
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• 2010

가상 세계는 현실과 유사하게 디자인된 가상 환경과 인간처럼 행동 하도록 설계된 agent들로 구성되어 있다. 이 agent는 입력된 행동들만 수행하는 기존의 시스템과는 달리, 자신의 감각 기관을 통해 지각된 정보를 자신이 가진 knowledge schema와 비교하여 판단한 후, Agent 스스로 행동하는 것이 특징이다. 이 과정에서 새로운 정보를 저장하기도 하고, 기존의 정보를 수정하기도 하며 때로는 실수를 범하기도 한다. 가상 세계에 존재하는 Agent는 지각, 인식, 판단, 행동의 단계를 끊임없이 반복한다. 이 가운데 '지각'의 주된 목적은 Agent의 인식 성공률을 높이는데 있다. 이것을 위해서는 인식에서 비교 가능한 최적의 데이터 형태로 지각의 데이터들을 전달해야한다. 이 연구에서 지각 단계의 데이터 구조는 어떻게 구성되어야하고 또, 어떤 방식으로 인식 단계에 전달되는지에 대해 소개할 것이다.

• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.298-319
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• 2002

The Semantic Web is a new technology that attempts to achieve effective retrieval, automation, integration, and reuse of web resources by constructing knowledge bases that are composed of machine-readable definitions and associations of resources that express the relationships among them. To have this kind of Semantic Web in place, it is necessary to have the following infrastructures: capability to assign unchangeable and unique identifier (URI) to each resource, adoption of XML namespace concept to prevent collision of element and attribute names defined by various institutions, widespread use of RDF to describe resources so that diverse metadata can be interoperable, use of RDF schema to define the meaning of metadata elements and the relationships among them, adoption of DAML+OIL that is built upon RDF(S) to increase reasoning capability and expressive power, and finally adoption of OWL that is built upon DAML+OIL by removing unnecessary constructors and adding new ones based on experience of using DAML+OIL. The purpose of this study is to describe the central concepts and technologies related to the Semantic Web and to discuss the benefits of metadata interoperability based on XML/RDF schemas and the potential applications of diverse ontologies.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.173-181
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• 2009

This paper proposes an algorithm to transform RDF(Resource Description Framework) models for ontology into CPN(Colored Petri Net) models. The algorithm transforms the semantics of the RDF model into the topology of the CPN by mapping the classes and the properties of the RDF onto the places of the CPN model then reflects the RDF statements on the CPN by representing the relationships between them as token transitions on the CPN. The basic idea of reflecting the RDF statements on the CPN is to generate a token, which is an ordered pair consisting of two tokens (one from the place mapped into the subject and the other one from the place mapped into the object) and transfer it to the place mapped into the predicate. We have actually built CPN models for given RDF models on the CNPTools and inferred and extracted answers to the RDF queries on the CPNTools.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.11-18
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• 2016

Linked Data is a web standard data definition method devised to connect, expand resources with a standardized type. Linked Data built in various areas expands existing knowledge through an open data cloud like LOD(Linked Open Data). A project to link and service existing knowledge through LOD is under way worldwide. However, LOD project in domestic is being participated in a specific field to the level of research. In this paper, we suggests a method to build the area of technical knowledge like legislations in type of Linked Data, and distribute such Linked Data built to LOD. The construction method suggested by this paper divides knowledge of legislations in structural, semantic, and integrated perspective, and builds each of them by converting to Linked Data according to the perspective. Also, such built Linked Legal Data prepares to link knowledge in a standardized type by distributing them onto LOD. Built Linked Legal Data are equipped with schema for link service in various types, and give help increase understand the access type to existing legal information.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.307-312
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• 2012

For semantic search methods to provide more accurate results than keyword-based search in a logical representation that uses a knowledge base are being studied. Than most of the user to use formal query language and schema used to interpret the meaning of a user keyword. In this paper, we propose to expand the user query for semantic search. In the proposed system, user query expansion component and a component to adjust the results to interpret user queries to take advantage of the knowledge base associated with a search term. Finally, a user query semantic interpretation, the proposed scheme to verify the experimental results of the prototype system is described.