• Journal of Korean Medical classics
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• v.22 no.3
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• pp.97-105
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• 2009

We in this paper have constructed herb and formula ontologies. Herb instances and formula instances can be distinguished by nature, used part, effect, disease pattern, symptom, and formula and constituent herb, dosage, effect, disease pattern, symptom, and medical book, respectively. The knowledge for herbs and formulas in ontology is formalized with the distinguishable elements and their relations. Based on the herb and formula ontologies, we propose the three reasoning rules as follows: In herb ontology, the relation between herb and disease can be reasoned if there are the relation between herb and effect, and effect and disease. In formula ontology, there are two reasoning rules. First, if each constituent herb, dosage, effect, disease pattern, and symptom of two formulas is same, it can be reasoned that two formulas are same though the medical books of the formulas are different. Second, if each constituent herb and dosage is same in two formula, it can be reasoned that each formula has all of effects, disease patterns, and symptoms of formulas. In future study, we study other ontologies such as disease ontology with respect to Korean Medicine and define the reasoning rules about the ontologies.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.526-535
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• 2005

Ontology is a methodology on describing specific concepts and their relationships, and it is being considered important more and more as semantic web and variety of knowledge management systems are being highlighted. Ontology uses the relationships among concerts to represent some concrete semantics of specific concept. When we want to get some useful information from ontology, we severely have to process the transitive relationships because most of relationships among concepts represent transitivity. Technically, it causes recursive calls to process such transitive closure queries with heavy costs. This paper describes the efficient technique for processing transitive closure queries in ontology. To the purpose of it, we examine some approaches of current systems for transitive closure queries, and propose a technique by graph labeling scheme. Basically, we assume large size of ontology, and then we show that our approach gives relative efficiency in processing of transitive closure, queries.

• Journal of KIISE:Software and Applications
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• v.35 no.7
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• pp.431-441
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• 2008

The academic information analysis service is including automatic recommendation of reviewers and analysis of researchers' accomplishments. The service of recommendation of reviewers should be processed in a transparent, fair and accountable way. When selecting reviewers, the following information must be considered: subject of project, reviewer's maj or, expertness of reviewer, relationship between applicant and reviewer. The analysis service of researchers' accomplishments is providing statistic information of researcher, institution and location based on accomplishments including book, article, patent, report and work of art. In order to support these services, we designed ontology for academic information, converted legacy data to RDF triples, expanded knowledge appropriate to services using OntoFrame. OntoFrame is service framework which includes ontology, reasoning engine, triple store. In our study, we propose the design methodology of ontology and service system for academic information based on OntoFrame. And then we explain the components of service system, processing steps of automatic recommendation of reviewers and analysis of researchers' accomplishments.

• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.24-34
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• 2015

With the development of the semantic web, a large amount of data being produced nowadays is in RDF format. RDF is represented by a triple. An RDF database consisting of triples requires the high cost of join query processing. Materialized view is known as a scheme to reduce the query processing cost by accessing materialized views without accessing the database. It is physically stored the results or the intermediate results of the query processing in a storage area. In this paper, we propose a materialized view selection scheme by using decision tree to solve such a problem. The decision tree considers the size and maintenance costs of the materialized view as well as the profit of query response times. It is shown through performance evaluation that the proposed scheme increases the number of materialized views in the limited storage space and decreases the update rates of the materialized views.

• Journal of KIISE
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• v.43 no.4
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• pp.470-479
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• 2016

As the number of various types of media data such as UCC (User Created Contents) increases, research is actively being carried out in many different fields so as to provide meaningful media services. Amidst these studies, a semantic web-based media classification approach has been proposed; however, it encounters some limitations in video classification because of its underlying ontology derived from meta-information such as video tag and title. In this paper, we define recognized objects in a video and activity that is composed of video objects in a shot, and introduce a reasoning approach based on description logic. We define sequential rules for a sequence of shots in a video and describe how to classify it. For processing the large amount of increasing media data, we utilize Spark streaming, and a distributed in-memory big data processing framework, and describe how to classify media data in parallel. To evaluate the efficiency of the proposed approach, we conducted an experiment using a large amount of media ontology extracted from Youtube videos.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.3
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• pp.275-283
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• 2005

Ontologies are the core components of the Semantic Web and knowledge-based systems. But it is difficult to find useful ontologies in actual domains. In order to build useful domain ontology, the conceptualization of the domain knowledge by knowledge experts of the specific domain and the specification of conceptualized knowledge with formal languages by ontology designers are required. In addition, structured and detailed guidelines and methods should be provided to be shared by the development team members. However, existing ontology building methodologies define and describe the skeletal structure of the whole building process at the top-layer. We build a useful academic ontology that is based on the conceptual knowledge structure in the domain of philosophy, and propose a detailed methodology to build a text ontology based on Topic Maps. Our methodology consists of two phases, ontology modelling and ontology implementation. We implement a philosophy knowledge portal to support retrieving and navigating of the philosophy knowledge.

• Journal of Korean Society of Archives and Records Management
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• v.17 no.4
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• pp.177-200
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• 2017

In a new technological environment such as big data and AI, LOD will link record information resources with various data from both inside and outside. At the heart of this connection is the interlinking technology, and interlinked LOD will realize the opening of record information as the highest level of open data. Given the ever-increasing amount of records, automation through interlinking algorithms is essential in building LODs. Therefore, this paper analyzed the structure of record information interlinking with the external data and characteristics of the record information to be considered when interconnecting. After collecting samples from the CAMS data of the National Archives, we constructed a record information's LOD. After that, we conducted a test bed that automatically interlinks the personal information of the record metadata with DBPedia. This confirms the automatic interlinking process and the performance and accuracy of the automation technology. Through the implications of the testbed, we have identified the considerations of the record information resources of the LOD interlinking process.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.772-774
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• 2017

Currently, there are many simple searches for local culture and tourism, but systematic information retrieval using ontology technology is weak. The keyword-based search, which is an existing search method, derives a search result that is different from a user's wanted intention. On the other hand, semantic search using ontology constructs shows the information related to the search term by creating a relation between words and words. Therefore, when tourists search for cultural and tourist attractions in the area, they provide information that includes meaning relevance in the search results. If the ontology provides information on the culture, sightseeing area, transportation, Can be more easily grasped. In this paper, we propose an ontology-based retrieval system based on culture and tourist sites utilizing public institutions database by using mobile application by extending search system which relied only on existing internal database to provide accurate and reliable information to users. This efficient structure of the ontology makes it possible to provide information suitable for the user quickly and accurately.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.949-956
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• 2017

Visual interfaces of news sites look similar while their HTML have lots of different specifications and qualities. It's getting more and more significant to describe HTML semantically to make every computer able to understand contents to be shared as HTML5 specification refers. In this study, I have analysed HTML codes of 110 korean news sites in comparison to those of 8 global news sites. As results, 68% of news sites are still described in HTML4 specifications and only 10 out of 110 are in HTML5 specification and as high quality and strong semantics as global news sites. The result shows most korean news sites platforms had not been changed since they developed in mid-2000 and it's needed to be upgraded as language translation technologies are making it possible to share korean digital contents with the rest of world.

• Annual Conference on Human and Language Technology
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• 2006.10e
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• pp.189-196
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• 2006

본 논문은 시맨틱 웹 응용 서비스를 구현함에 있어 필수적으로 요구되는 온톨로지 인스턴스 구축을 효율적으로 처리하는 데 있어 텍스트 처리 기술이 어떤 역할을 수행할 수 있는 가를 $OntoFrame-K^{(R)}$라는 시맨틱 웹 기반 정보 유통 체계에의 적용 사례를 통해 살펴본다. 본 논문에서 소개하는 텍스트 처리 기술은 개체 확인물 통한 개념 사례화, 주제 분야 할당을 통한 메타데이터 확장에, 그리고 인용 정보 추출 및 인용 관계 구축을 통한 객체 관계속성 구축에 적용된다. 개체 확인에서는 메타데이터 비교 잊 병합을 사용하였으며 이를 기반으로 한 수작업 구축을 통해 8,543명의 인력 URI를 확보하였다. 주제 및 분야 할당에서는 색인어와 분야분류명이 매핑된 시소러스 개념어의 매칭을 통해 색인어 별 TF (Term Frequency), 색인어와 매칭된 개념어 별 TF, 색인어와 매칭된 개념어 별 시소러스에서의 깊이, 색인어와 매칭된 개념어 별 개념 패싯, 색인어와 매칭된 각 개념어에 부착된 분야분류명 목록 등 할당을 위한 다양한 자질을 확보 적용하였다. 인용 정보 추출과 인용 관계 구축에서는 객체 URI와 인력 URI를 기반으로 하여 자동 추출된 인용 정보를 반영하는 방식으로 7,237개 문헌으로부터 총 135개의 인용 네트워크 그룹을 자동으로 확보하였다. 본 연구를 통해 제시된 텍스트 처리 기술의 활용 방안이 향후 시맨틱 웹 응용 서비스 및 인프라 구현에서 다각적으로 활용될 수 있기를 기대한다.