• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.247-256
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• 2008

This research is to develop product retrieval system through simplified communication by applying intelligent agent technology based on automatically created domain ontology to present solution on problems with e-commerce system which searches in the web documents with a simple keyword. Ontology development extracts representative term based on classification information of international product classification code(UNSPSC) and jewelry websites that is applied to analogy relationship thesaurus to establish standardized ontology. The intelligent agent technology is applied to retrieval stage to support efficiency of information collection for users by designing and developing e-commerce system supported with semantic web. Moreover, it designs user profile to personalized search environment and provide personalized retrieval agent and retrieval environment with inference function to make available with fast information collection and accurate information search.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.819-828
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• 2007

In this paper, we propose a topic maps matching and merging approach based on the syntactic or semantic characteristics and constraints of the topic maps. Previous schema matching approaches have been developed to enhance effectiveness and generality of matching techniques. However they are inefficient because the approaches should transform input ontologies into graphs and take into account all the nodes and edges of the graphs, which ended up requiring a great amount of processing time. Now, standard languages for developing ontologies are RDF/OWL and Topic Maps. In this paper, we propose an enhanced version of matching and merging technique based on topic partitioning, several matching operations and merging conflict detection.

• Journal of KIISE:Software and Applications
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• v.33 no.1
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• pp.114-129
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• 2006

Ontology mapping is the task of finding semantic correspondences between two ontologies. In order to improve the effectiveness of ontology mapping, we need to consider the characteristics and constraints of data models used for implementing ontologies. Earlier research on ontology mapping, however, has proven to be inefficient because the approach should transform input ontologies into graphs and take into account all the nodes and edges of the graphs, which ended up requiring a great amount of processing time. In this paper, we propose a multi-strategic mapping approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the topic maps. Our multi-strategic mapping approach includes a topic name-based mapping, a topic property-based mapping, a hierarchy-based mapping, and an association-based mapping approach. And it also uses a hybrid method in which a combined similarity is derived from the results of individual mapping approaches. In addition, we don't need to generate a cross-pair of all topics from the ontologies because unmatched pairs of topics can be removed by characteristics and constraints of the topic maps. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Yahoo german literature dictionary as input ontologies. Our experiments show that the automatically generated mapping results conform to the outputs generated manually by domain experts, which is very promising for further work.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.871-876
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• 2015

Recently, the Web is becoming more difficult to manage efficiently retrieve with the increase of data. However, the retrieval systems that are currently used have not been applied to the Semantic Web technology. Thus, the development of the Semantic Web is not activated. User of the retrieval system also the Semantic Web usage is low is the situation. In this paper, we are analyzed the retrieval system that is currently being used. we are proposed added the rule of the RDF representation during ontology implementation of the retrieval system. And we propose the user-centric of retrieval system design and implementation.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.97-106
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• 2007

A core technology that may realize the Semantic Web is Ontology. The OWL (Web Ontology Language) has been positioned as a standard language. It requires technical expertise to directly represent the domain knowledge in OWL. Based on our experience of analyzing the fundamental relationships of concepts in e-catalog domain, we have developed a visual product information modeler called PROMOD. The modeling editor makes it possible to automatically generate the OWL codes for the given product information. We employ an Extended Entity-Relationship for conceptual modeling, enriched with modeling elements specialized for the product domain. In this paper, we present our translation schemes from EER model to OWL codes, and how to design and implement the modeling editor. We also provide a scenario to demonstrate the usage of the editor in practice.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.525-534
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• 2006

Ontology specifies the knowledge in a specific domain and defines the concepts of knowledge and the relationships between concepts. It is possible to provide the service based on the semantic web through the ontology. Therefore, to specify and define the knowledge in a specific domain, it is required to generate the ontology which conceptualizes the knowledge. Accordingly, to search the information of potential customers for home-delivery marketing of post office, we design the specific domain to generate the ontology based on the semantic web in this paper. And we propose how to retrieve the information, using the generated ontology. We implement the data search robot which collects the information based on the generated ontology. Also, we confirm that the ontology and the search robot perform the information retrieval exactly.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.331-335
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• 2008

시맨틱 웹은 정보의 의미를 개념으로 정의하고 개념들 간의 관계성을 표현함으로써, 문서들 간의 단순 연결이 아닌 의미 연결을 통해서 보다 정확하고 효율적인 정보 검색이 가능하게 된다. 이러한 시맨틱 웹의 비전이 구체화되기 위해서는 웹 온톨로지(Web Ontology)를 기반으로 의미 정보로 구성된 시맨틱 문서들에 대한 추론을 통해서 웹상에 존재하는 엄청난 정보들 간의 관련성을 파악하고 사용자가 요구하는 정보를 보다 효율적으로 검색할 수 있는 시스템이 필수적이다. W3C에서 제안한 OWL은 대표적인 온톨로지 언어이다. 시맨틱 웹 상에서 OWL 데이타를 효율적으로 검색하기 위해서는 잘 구성되어진 저장 스키마를 구축해야 한다. 본 논문에서는 Jena2의 경우, 단일 테이블에 문서의 정보를 저장하기 때문에 단순 선택 연산 (Simple Selection), 조인 연산이 요구되는 질의에 대한 성능이 저하되고 대용량의 OWL데이터의 처리에 있어 성능이 저하되는 문제를 해결하기 위하여 본 논문에서는 OWL 문서의 의미를 Class, Property, Individual로 분류하여 각각의 데이터 정보들을 테이블에 저장하기 위한 다중 변환기와 OWL 변환기 기능을 가진 시멘텍 검색 엔진을 설계 및 구현하였다. 본 검색 엔진을 테스트한 결과, 단순정보검색 질의 시 Jena2에서 비정규화된 테이블 구조로 저장할 때보다 질의 응답 속도를 향상 시킬 수 있었고, 조인 연산 시 두 테이블의 크기로 인한 조인비용이 발생하는 문제점을 해결함으로써 빠른 검색 및 질의 속도를 보장할 수 있었다.

• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.397-400
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• 2009

현재 웹은 단순히 정보를 수집하여 제공하던 웹 1.0을 지나 정보의 사용자가 곧 생산자가 되어 개방된 웹 환경을 기반으로 사용자 스스로 콘텐츠를 제작, 재창조, 공유하는 인터넷 서비스 모델인 웹 2.0으로 발전하였다. 이러한 웹의 발전 과정에서 시맨틱 웹이 등장하게 되었고 시맨틱 웹이 지리 정보와 접목되어 시맨틱 지리 정보 시스템이 등장하게 되었다. 기존 지리 정보 시스템에서는 사용자들이 국한된 정보만을 제공받아 왔지만 웹이 발전하고 수많은 콘텐츠가 생성되면서 웹의 데이터를 지리 정보 시스템과 연결시켜서 사용자에게 풍부한 정보를 제공 할 수 있는 시스템이 연구, 개발되고 있다. 하지만 기존 연구들은 사용자가 시스템에 접속하여 비공간 정보를 입력해야 하는 특정 시스템에 종속적이라는 단점을 가지고 있어 시맨틱 웹에서 지향하는 풍부한 서비스 제공에 어려움을 격고 있다. 따라서 이 논문에서는 웹 자원을 정의된 지리정보 온톨로지(Geo-Ontology)의 인스턴스로 추가하여 지리 정보 시스템의 비공간 정보를 확장함으로써 특정 시스템에 종속적이지 않고 사용자에게 보다 풍부한 서비스를 제공하기 위한 모델을 제안하고 프로토타입을 구현한다.

• The KIPS Transactions:PartD
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• v.14D no.2
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• pp.203-210
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• 2007

Ontology can be used as a formal and demonstrative knowledgebase that can express the thinking process of human. Software Development Process is a collection of ideal practices and procedural system that is performed by mature organization with high capability. Due to complexity of process, however, Software development Process often results in obstruction of introducing and improving simple process activity. While introducing and improving software development process, application of ontology to complex software development process is more approachable by showing deductive results of relationship between ISO/IEC 15504 and CMMI. In this paper, we demonstrate a methodology that utilizes the improved process database conceptually mapping between ISO/IEC 15504 and CMMI using ontology.