• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.95-110
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• 2006

To enhance the rule-based reasoning capability of Semantic Web, the XRML (eXtensible Rule Markup Language) approach embraces the meta-information necessary for the extraction of explicit rules from Web pages and its maintenance. To effectuate the automatic identification of rules from unstructured texts, this research develops a framework of using rule ontology. The ontology can be acquired from a similar site first, and then can be used for multiple sites in the same domain. The procedure of ontology-based rule identification is regarded as a graph search problem with incomplete nodes, and an A* algorithm is devised to solve the problem. The procedure is demonstrated with the domain of shipping rates and return policy comparison portal, which needs rule based reasoning capability to answer the customer's inquiries. An example ontology is created from Amazon.com, and is applied to the many online retailers in the same domain. The experimental result shows a high performance of this approach.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.151-173
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• 2005

We developed a methodology of rule acquisition from texts such as Web pages which utilizes ontology in identification of rule components. We expect that the proposed methodology can reduce the bottleneck of rule acquisition and contribute to the utilization of rule based systems. As parts of our research, we designed an ontology for rule acquisition named OntoRule and proposed a rule acquisition methodology through OntoXRML which is an acquisition tool using OntoRule. Also, we evaluated our approach by calculating missed recommendations and wrong recommendations of rule components in rule acquisition experiments over three online bookstores.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.91-103
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• 2010

This paper introduces efficient rule-based semantic search techniques to ontology-based knowledge commerce services. Primarily, the search techniques presented in this paper define rules of reasoning that are required for users to search using the concept of ontology, multiple characteristics, relations among concepts and data type. In addition, based on the defined rules, the rule-based reasoning techniques search ontology for knowledge commerce services. This paper explains the conversion rules of query which convert user's query language into semantic search words, and transitivity rules which enable users to search related tags, knowledge products and users. Rule-based sematic search techniques are also presented; these techniques comprise knowledge search modules that search ontology using validity examination of queries, query conversion modules for standardization and expansion of search words and rule-based reasoning. The techniques described in this paper can be applied to sematic knowledge search systems using tags, since transitivity reasoning, which uses tags, knowledge products, and relations among people, is possible. In addition, as related users can be searched using related tags, the techniques can also be employed to establish collaboration models or semantic communities.

• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.97-105
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• 2016

With the increasing demand for interoperability among existing learning resource systems in order to enable the sharing of learning resources, such resources need to be annotated with ontologies that use different metadata standards. These different ontologies must be reconciled through ontology mediation, so as to cope with information heterogeneity problems, such as semantic and structural conflicts. In this paper, we propose an ontology-mapping technique using Semantic Web Rule Language (SWRL) to generate semantic mapping rules that integrate learning resources from different systems and that cope with semantic and structural conflicts. Reasoning rules are defined to support a semantic search for heterogeneous learning resources, which are deduced by rule-based inference. Experimental results demonstrate that the proposed approach enables the integration of learning resources originating from multiple sources and helps users to search across heterogeneous learning resource systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.875-880
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• 2005

OWL(Web Ontology Language) is the Ontology Standard Language and the a lot of Ontologies are being constructed in OWL. But the research on the extension of OWL is also progressing because of the limit of representation power of in OWL language. The W3C suggests the SWRL(Semantic Web Rule Language) based on the combination of OWL and RuleML(Rule Markup Language), which is improved in the representation of rule. Thus, both OWL and SWRL are used for developing ontologies. However, research on inference of ontologies written in both languages is just begun. These day, for the inference of ontologies written in both languages, ontologies and divided in to two parts. The part written in OWL and written in SWRL. For the inference of the part written in OWL, Racer, a DL based inference engine, is used and for the other part Jess, a rule-based engine, is used. In this paper, we will propose three methods for integrated inference of the OWL part and the SWRL part of ontologies using Jess and some tools for ontology inference : OWLJessKB and SWRL Factory

• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.6-11
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• 2018

With the development of the Internet of Things technology, a system that ensures the self-adaptability of an environment that includes various IoT devices is attracting public attention. The rules for determining behavior rules in existing self-adaptation systems are based on the assumption of changes in system members and environment. However, in the IoT environment, flexibility is required to determine the behavior rules of various types of IoT devices that change in real time. In this paper, we propose a rule configuration in a self-adaptive system using SWRL based on OWL ontology. The self-adaptive system using the OWL - SWRL rule configuration has two advantages. The first is based on OWL ontology, so we can define the characteristics and behavior of various types of IoT devices as an integrated concept. The second is to define the concept of a rule as a specific language type, and to add, modify and delete a rule at any time as needed. Through the rule configuration in the adaptive system, we have shown that the rule defined in SWRL can provide flexibility and deeper concept expression function to adaptability to IoT environment.

• Journal of the Korean Society for information Management
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• v.24 no.3
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• pp.119-147
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• 2007

Actually a diffusion of a semantic web application and utilization are situations insufficient extremely. Technology most important in semantic web application is construction of the ontology which contents itself with characteristics of semantic web. Proposed a suitable a method of building web ontology for characteristics or semantic web and web ontology as we compared the existing ontology construction ana ontology construction techniques proposed for web ontology construction, and we analyzed. And modeling old ontology to bases to description logic and the any axiom rule that used an expression way of SWRL, and established inference-based web ontology according to proposed ways. Verified performance of ontology established through ontology inference experiment. Also established an web ontology-based intelligence image retrieval system, to experiment systems for performance evaluation of established web ontology, and present an example of implementation of a semantic web application and utilization. Demonstrated excellence of a semantic web application to be based on ontology through inference experiment of an experiment system.

• Journal of the Korean Society for information Management
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• v.25 no.1
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• pp.149-171
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• 2008

Actually a diffusion of a Semantic Web application and utilization are situations insufficient extremely. Technology most important in Semantic Web application is construction of the Ontology which contents itself with characteristics of Semantic Web. Proposed a suitable a Method of Building Web Ontology for characteristics of Semantic Web and Web Ontology as we compared the existing Ontology construction and Ontology construction techniques proposed for Web Ontology construction, and we analyzed. And modeling did Ontology to bases to Description Logic and the any axiom rule that used an expression way of SWRL, and established Inference-based Web Ontology according to proposed ways. Verified performance of Ontology established through Ontology inference experiment. Also, established an Web Ontology-based Intelligence Image Retrieval System, to experiment systems for performance evaluation of established Web Ontology, and present an example of implementation of a Semantic Web application and utilization. Demonstrated excellence of a Semantic Web application to be based on Ontology through inference experiment of an experiment system.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.814-820
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• 2008

Recently, researches on ontology-based pattern classification have been tried out in many fields. However, in most of the researches, the ontology which represents the knowledge about pattern classification is just referred during the processes of the pattern classification. In this paper, we propose ontology-based fuzzy classifier for pattern classification which is extended from the fuzzy rule-based classifier In order to realize the proposed classifier, we construct an ontology by conceptualizing the method of fuzzy rule-based pattern classification and generate ontology inference rules for pattern classification. Lastly, we show the validity o) the proposed classifier through the experiment of pattern classification on the Fisher's IRIS dataset.

• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.401-410
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• 2009

In order to derive hidden information (concept subsumption, concept satisfiability and realization) of OWL ontology, a number of OWL reasoners have been introduced. The most of these ontology reasoners were implemented using the tableau algorithm. However most reasoners simply report this information without providing a justification for any arbitrary entailment and unsatisfiable concept derived from OWL ontologies. The purpose of this paper is to investigate an optimized method for non-deterministic rule of the tableau algorithm and finding axioms to cause inconsistency in ontology. In this paper, therefore, we propose an optimized method for non-deterministic rule and finding axiom to cause inconsistency using NATMS. In the first place, we introduce Dependency Directed Backtracking to deal non-deterministic rule, a tableau-based decision procedure to find unsatisfiable axiom Furthermore we propose an improved method adapting NATMS.