• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.223-230
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• 2020

Companies have made an investment of cost and time to optimize processing of a new business model in a cloud environment, applying collaboration technology utilizing business processes in a social network. The collaborative processing method changed from traditional BPM to the cloud and a mobile cloud environment. We proposed a collaborative system for operating processes in social networks using MOXMDR-DAI+ (eXtended Metadata Registry-Data Access & Integration based multimedia ontology). The system operating cloud-based collaborative processes in application of MOXMDR-DAI+, which was suitable for data interoperation. MOXMDR-DAI+ applied to this system was an agent effectively supporting access and integration between multimedia content metadata schema and instance, which were necessary for data interoperation, of individual local system in the cloud environment, operating collaborative processes in the social network. In operating the social network-based collaborative processes, there occurred heterogeneousness such as schema structure and semantic collision due to queries in the processes and unit conversion between instances. It aimed to solve the occurrence of heterogeneousness in the process of metadata mapping using MOXMDR-DAI+ in the system. The system proposed in this study can visualize business processes. And it makes it easier to operate the collaboration process through mobile support. Real-time status monitoring of the operation process is possible through the dashboard, and it is possible to perform a collaborative process through expert search using a community in a social network environment.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2001.11a
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• pp.169-171
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• 2001

본 논문에서는 XML(eXtensible Markup Language)을 위한 데이터 모델을 제시하기 위해 현재 광범위하게 사용되고 있는 관계형 데이터베이스(relational database) 개념을 적용한다. 관계형 데이터베이스는 업무 요구사항의 분석으로부터 고수준의 개념적 데이터 모델을 사용해서 데이터베이스에 대한 개념적 스키마(conceptual schema)를 생성한 다음, 고수준 개념적 데이터 모델을 구현 데이터 모델로 변환하여 논리적 데이터베이스 스키마를 생성한다. 이때, 고수준 개념적 데이터 모델링의 대표적인 방법으로 ER모델을 사용하고, 구현 데이터 모델로 관계 모델(relation model)을 사용한다. XML은 문서의 논리적 구조를 정의하는 DTD와 XML Schema 등을 갖는다. XML의 DTD와 정보 모델링 기법인 E/R 모델은 모두 작은 세계(real world)를 모델링하는 도구들이라고 할 수 있다. 본 논문에서는 XML의 DTD와 E/R 모델의 구성요소들을 분석하여 서로 사상(mapping)시키는 'XML을 위한 데이터 모델(A Data Model for XML)'을 제시한다. 최종적으로 제시된 XML을 위한 데이터 모델에 의해 작은 세계(real world)을 모델링하는 XML DTD에서 정의한 구조(XML Structure)을 따르는 유효한 XML문서(validate XML document)들은 관계형 데이터베이스에 저장할 수 있게 된다.

• Journal of Korea Multimedia Society
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• v.11 no.7
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• pp.940-955
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• 2008

Semantically similar XML documents in the same application domain might often conform to different schemas. To uniformly view and query such XML documents, we need an efficient method of integrating XML schemas. This paper proposes a sophisticated method for integrating XML schemas in the same application domain. To compute mapping relationships between schemas, the proposed method utilizes various relationships, such as synonyms and hypernyms, between lexical items based on dictionaries and domain ontologies. Particularly, the relationships between lexical items are elaborated by taking their structural information into account. In addition, this paper proposes a more accurate method for integrating compositors. Experimental results with schemas in various application domains show that the utilization of domain ontologies and the structural relationships between lexical items enhance the precision and recall of integrated schemas.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.195-202
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• 2002

Information exchange on XML such as B2B electronic commerce is spreading. Therefore the systematic and stable management mechanism for storing the exchanged information is needed. For this goal there are many research activities for connection between XML application and relational database. But because XML data have hierarchical structures and relational database can store only flat-structured data, we need to store XML data in object-oriented database that support hierarchical structure. Accordingly the modeling methodology for storing XML data in object-oriented database is needed. In this parer, the transforming methods based on object model from XML DTD to object-oriented database schema is proposed. For this, we first introduce mapping methods that map XML DTD to object model and then we propose soem methods that transform from the object model to object-oriented database schema.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.333-342
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• 2010

Building ontology is the key factor to construct semantic web. However, this is time-consuming process. Hence, there are several approaches which automatically generate the ontologies from relational databases. Current studies on the automatic generation of the ontologies from relational database are focused on generating the ontology by analyzing the database schema and stored data. These studies generate the ontology by analyzing only tables and constraints in the schema and ignore view definitions. However, view definitions are defined by a database designer considering the domain of the database. Hence, by considering view definitions, additional classes and hierarchical relationships can be generated. And these are useful in answering queries and integration of ontologies. In this paper, we formalize the generation of classes and hierarchical relationships by analyzing existing methods, and we propose the method which generates additional classes and hierarchical relationships by analyzing view definitions. Finally, we analyze the generated ontology by applying our method to synthetic data and real-world data. We show that our method generates meaningful classes and hierarchical relationships using view definitions.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.701-714
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• 2009

In the enterprises the data integration based on service requires integrated data management as the change in the environment of enterprises accelerates. Cooperation among enterprises is accomplished through accessing distributed database using business process. As this approach is performed based on the global query, problems such as data heterogeneity, schema heterogeneity, and verification of validity have to be solved in advance for the interoperability among the heterogeneous system. Thus, cooperation requires dynamic and reliable construction. In this paper, we propose XMDR-DSM (eXtended MetaData Registry-Data Service Mediator) system for cooperation. XMDR-DSM, which is comprised of XMDR-DS, XMDR-DQP, and XMDR-DAI, supports the mapping between global schema and local schema and provides data access and integration service. Therefore, XMDR-DSM enables the mutual support of business operations among heterogeneous database. In addition, it can secure information as reusable asset and the standardization of interchange. Also it can manage unified information since it provides business process based on workflow; therefore, it will be able to increase the life span of information and reduce the cost.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.66-71
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• 2007

멀티미디어 데이터에 대한 효율적인 검색을 지원하기 위해 제정된 MPEG7이나 TV-AnyTime 등의 표준들은 XML을 사용하여 Metadata를 효과적으로 표현할 수 방법을 제시하고 있다. 플랫폼에 독립적으로 사용가능하다는 XML의 강점에도 불구하고 Text 방식으로 데이터를 저장하기 때문에 보안에 취약할 수밖에 없으며, 대용량의 자료 처리에도 문제점을 드러낸다. 이를 보완하기 위하여 XML 문서를 RDBMS에 저장하는 방법들이 제안되고 있는데, 기존의 Model Mapping이나 Structure Mapping의 경우 노드 검색을 위해 Traversing을 할 경우 많은 조인이 필요하기 때문에 한정된 메모리와 낮은 처리능력을 갖춘 임베디드 멀티미디어 플랫폼에서는 비효율적일 수밖에 없다. 본 논문에서는 MPEG7 Metadata를 RDBMS에 저장하고, 이를 검색할 때, 조인의 횟수를 최소화할 수 있는 저장 모델을 제안하고 있다. 부모, 자식, 형제간의 노드를 효율적으로 검색할 수 있도록 path MetaSchema를 제안함으로써, 최소 1번의 검색으로 필요한 노드 정보들을 추출할 수 있도록 하였다. 그리고 Annotation 작성시에 XML의 Attribute와 Element로 삽입하였기에, 기존의 방법에서 Annotation을 분석하기 위해 필요했던 Annotation 파싱을 제거하고, SAX나 DOM을 사용할 수 있도록 제안함으로써, Annotation의 정보에 대한 접근이 효율적으로 개선되었다.

• Journal of KIBIM
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• v.13 no.2
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• pp.37-46
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• 2023

The main objective of this study is to propose a method to enhance building safety using the Industry Foundation Classes (IFC) schema in Building Information Modeling (BIM). To achieve this goal, a fire object relationship diagram is created by using the Model View Definition (MVD) and Property Set (Pset) methodology, as well as the Work Breakdown Structure (WBS) based object relationship analysis. The proposed method illustrates how to represent objects and tasks related to fire prevention and human safety during a building fire, including variables that are relevant to these aspects. Furthermore, the proposed method offers the advantage of considering both the IFC object hierarchy and the project work hierarchy when creating new objects, thereby expanding the attribute information for fire safety and maintenance. However, upon confirmation via an IFC viewer after development, a problem with the accuracy of mapping between attributes and objects arises due to the issue of proxy representation of related object information and newly added object information in standard IFC. Therefore, in future research, a mapping method for fire safety objects will be developed to ensure accurate representation, and the scope of utilization of the fire safety object diagram will be expanded. Furthermore, efforts will be made to enhance the accuracy of object and task representation. This research is expected to contribute significantly to the technological development of building safety and fire facility design in the future.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.879-890
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• 2000

Designing a multilevel database application is a complex process, and the entities and their associated security levels must be represented using an appropriate model unambiguously. It is also important to capture the semantics of a multilevel databse application as accurate and complete as possible. Owing to the focus of the IDEA Methodology for designing the non-secure database applications on the data-intensive systems, the Object Model describes the static structure of the objects in an application and their relationships. That is, the Object Model in the IDEA Methodology is an extended Entity-Relationship model giving a static description of objects. The IDEA Methodology has not been developed the multilevel secure database applications, but by using an existing methodology we could take advantage of the various techniques that have already been developed for that methodology. That is, this way is easier to design the multilevel secure schema than to develop a new model from scratch. This paper adds the security features 새？ Object Model in the IDEA Methodology, and presents the transformation from this model to a multilevel secure object oriented schema. This schema will be the preliminary work which can be the general scheme for the automatic mapping to the various commercial multilevel secure database management system such as Informix-Online/Secure, Trusted ORACLE, and Sybase Secure SQL Server.