• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.501-502
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• 2011

국가R&D정보는 R&D과제, 참여인력, 성과, 장비정보등으로 구성되며, 특히 R&D과제의 참여인력정보를 기반으로 한 의미기반서비스를 위해서는 인력 온톨로지의 모델링이 중요하다. 온톨로지 모델링을 어떻게 하느냐에 따라서 구현 가능한 의미기반서비스의 범위가 달라지며, 구성하는 데이터에 대한 이해도와 서비스 종류에 따라 모델링을 다르게 할 수 있다. 국가R&D인력정보기반 의미기반서비스는 인력정보의 현황과 특성에 대한 이해를 통해 연구자들이 협력대상 연구자와 평가위원 후보를 쉽고 효율적으로 탐색 활용할 수 있는 정보이용환경을 제공하는 것을 목표로 한다. 본 논문에서는 보다 지능화된 의미기반 추론서비스 제공을 위한 국가 R&D 인력정보의 온톨로지 모델링 및 활용 사례를 제시하고자 한다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.457-462
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• 2007

시멘틱 웹에서의 온톨로지는 특정 영역의 설명을 위해 공유할 개념화된 명세란 정의로 널리 알려져 있으며, 시멘틱웹의 중요한 요소기술이다. 온톨로지는 특정 도메인에 대한 정보를 기술하는데, 이러한 온톨로지를 매핑할 경우 많은 양의 정보를 통합관리하거나, 상호호환성을 이룰 수 있다. 여러 온톨로지 매핑 방법론의 성능을 평가하는 수단 중 f-measure란 것이 있는다. f-measure의 값은 정확도(precision)과 응답률(recall)에 의해서 결정된다. 정확도와 응답률이 변화함에 따라 f-measure 값도 자연히 변하기 때문에, 높은 f-measure 값을 구하기 위해서는 정확도와 응답률의 밸런스를 조정할 필요가 있다. 본 논문에서는 높은 f-measure값을 얻을 수 있는 정확도와 재현률을 구하는 방법을 휴리스틱적 방법을 통하여 알아보고자 한다.

• Journal of the Korean Society for information Management
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• v.22 no.2 s.56
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• pp.41-56
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• 2005

For the purpose of extending the Web that is able to understand and process information by machine, Semantic Web shared knowledge in the ontology form. For exquisite query processing, this paper proposes a method to use semantic relations in the ontology as relevance feedback information to query expansion. We made experiment on pharmacy domain. And in order to verify the effectiveness of the semantic relation in the ontology, we compared a keyword based document retrieval system that gives weights by using the frequency information compared with an ontology based document retrieval system that uses relevant information existed in the ontology to a relevant feedback. From the evaluation of the retrieval performance. we knew that search engine used the concepts and relations in ontology for improving precision effectively. Also it used them for the basis of the inference for improvement the retrieval performance.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.179-184
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• 2012

The ultimate purpose of cities is 'the enhancement of quality of life in city'. In order to achieve this, it is required to optimize the Ontology-driven ubiquitous services included in the U-City and UIS of regions and communities and so on. Almost U-Service's contents are related to spatial or temporal extent. So it is important to design Spatio-temporal event schema for efficient access to U-City. There is a rapid change into an urban society in the shape of Ontology-driven ubiquitous services in which a content on a region or an incident is newly reconstructed through various ideas with the influence of the ubiquitous environment.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.505-517
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• 2008

This paper proposes a rewriting algorithm of OWL-DL ontology query in SPARQL. Currently, to obtain inference results of given SPARQL queries, Web ontology repositories construct inference ontology models and match the SPARQL queries with the models. However, an inference model requires much larger space than its original base model, and reusability of the model is not available for other inferrable SPARQL queries. Therefore, the aforementioned approach is not suitable for large scale SPARQL query processing. To resolve tills issue, this paper proposes a novel SPARQL query rewriting algorithm that can obtain results by rewriting SPARQL queries and accomplishing query operations against the base ontology model. To achieve this goal, we first define OWL-DL inference rules and apply them on rewriting graph pattern in queries. The paper categorizes the inference rules and discusses on how these rules affect the query rewriting. To show the advantages of our proposal, a prototype system based on lena is implemented. For comparative evaluation, we conduct an experiment with a set of test queries and compare of our proposal with the previous approach. The evaluation result showed the proposed algorithm supports an improved performance in efficiency of the inferrable SPARQL query processing without loss of completeness and soundness.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.81-107
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• 2015

This study describes the Bottom-up method for implementation of an ontology system from the RDB. The STNet, a structured terminology glossary based on RDB, was served as a test bed for converting to RDF ontology, for generating the inference rules, and for evaluating the results of the semantic search. We have used protege editor of the ontology developing tool to design ontologies with test data. We also tested the designed ontology with the Inference Engine (Pellet) of protege editor. The generated reference rules were tested by TBox and SPARQL queries through STNet ontology. The results of test show that the generated reference rules were verified as true and STNet ontology were also evaluated to be useful for searching the complex combination of semantic relation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.9-20
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• 2011

Future warfare paradigm is changing to network-centric warfare and effects-based operations. In order to find first and strike the enemy in the battlefield, friendly unit requires real-time target acquisition, intelligence collection, accurate situation assessment, and timely decision. The rapid development in advanced sensor technology and wireless networks requires a significant change in operational concepts of the battlefield surveillance. In particular, the introduction of a battlefield surveillance sensor network system is a big challenge to the ground forces which have lack of automated information collection assets. Therefore this paper proposes an ontology-based context-aware framework for the battlefield surveillance sensor network system which is needed for early finding the enemy and visualizing the battlefield in the ground force operations. Compared with the performance of existing systems, the one of the proposed framework has shown highly positive results by applying the context systems evaluation method. The framework has also proven to be satisfactory by the structured evaluation method using device collaboration. Since the proposed ontology-based context-aware framework has a lot of advantages in terms of scalability and reusability, the ground force's reconnaissance and surveillance system can be widely applied to expand in the future. And, ontology-based model has some weak points such as ontology data size, processing time, and limitation of network bandwidth. However, these problems can be resolved by customizing properly to fit the mission and characteristics of the unit. Moreover, development of the next-generation communication infrastructure can expedite the intelligent surveillance and reconnaissance service and may be expected to contribute greatly to expanding the information capacity.

• Proceedings of the Korean Society for Information Management Conference
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• 2010.08a
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• pp.41-44
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• 2010

본 논문은 토픽맵 기반 온톨로지 시스템의 통합효과 측정을 위한 연구에 앞서 통합의 가능성과 통합 성능을 측정하기 위한 프로토타입 시스템 구축에 관한 연구이다. 프로토타입 시스템 구축을 통해 자동 통합 툴의 성능을 측정하고자 한다. 이를 위해 통합 전의 단일 토픽맵에서의 검색 결과와 통합 토픽맵에서의 검색 결과를 비교하여 정답율과 재현율을 평가함으로써 통합 토픽맵이 정보의 손실 없이 단일 토픽맵들을 완전히 통합한 것인지 확인할 수 있다.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.71-92
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• 2008

Currently, hotel search engines may help travelers find hotels, but the returned set of information is usually not satisfactory to them. It is because the engines do not understand what travelers want exactly and cannot deal with the travelers' interest which is expressed in various terms, even including some ambiguous ones. The objective of this research is to build hotel ontology using currently available semantic web technologies such as RDF, OWL and SWRL and to show how it can be used to help travelers find hotels of their interest. To that end, we analyzed available hotel-related ontologies and investigated typical terms which are used when searching for hotels in the Q&A communities. Based on the results of the analysis and investigation, we designed hotel domain ontology which consists of Objective Concepts Ontology(OCO), Universal Concepts Ontology(UCO), and Evaluation Concepts Ontology(ECO). To demonstrate the use of the ontology for a hotel search, we developed a Semantic Hotel Search System (SHSS).

• 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).