• Journal of Digital Convergence
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• v.11 no.6
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• pp.175-185
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• 2013

For effective information sharing, data provenance semantics need to be managed effectively. Based on a scheme to represent data provenance semantics, we propose a model to calculate information sharing costs. Information sharing costs are derived from probabilities of type I and type II errors that occur in organizational information sharing, costs related to these errors, and information sharing distances between organizational units which are determined by information sharing workflows. We apply the model to various types of information sharing workflows including departmental information systems, hierarchical information systems, a hub and a stand-alone system. The calculated information sharing costs show that the hub with data standardization is best in information sharing; however without standardization its information sharing cost deteriorates to that of a departmental information system. And, any information sharing workflow is better than a stand-alone system. It is proved that the model is useful in analyzing effectiveness of information sharing workflows and their characteristics.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.53-63
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• 2011

Many techniques have been proposed to store and query XML data efficiently. One way achieving this goal is using relational database by transforming XML data into relational format. It is important to transform schema to preserve the content, the structure and the constraints of the semantics information of the XML document. Especially, key constraints are an important part of database theory. Therefore, the proposal technique has considered the semantics of XML as expressed by primary keys and foreign keys. And, the proposal technique can preserve not only XML data constraints but also the content and the structure and the semantics of XML data thru transformation process. Transforming information is the content and the structure of the document(the parent-child relationship), the functional dependencies, semantics of the document as captured by XML key and keyref constraints. Because of XML schema transformation ensures that preserving semantic constraints, the advantages of these transformation techniques do not need to use the stored procedure or trigger which these data ensures data integrity in the relational database. In this paper, there is not chosen the ID/IDREF key which supported in DTD, the inheritance relationship, the implicit referential integrity.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.95-102
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• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency md requires many efforts of system administrator or annotator because of imperfect automatic processing. In this paper, we propose semantics-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method and optimized comparison area extracting that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantics-based retrieval.

• The Journal of Society for e-Business Studies
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• v.5 no.1
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• pp.1-18
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• 2000

As the networks (i.e., intranet and internet) proliferate all over the world, it is inevitable to move some (or all) of the enterprise activities into virtual spaces. Differently from business data, product data have complex semantics and thus are not properly exchanged among different application programs. Even though some neutral formats of product data have been developed by standard organizations, translating them among various application programs still needs the comprehensive understanding of the complex semantics. Recently, it is widely recognized that capturing more knowledge is the next step In overcome the current difficulties on sharing product data. In this paper, we present Web-based knowledge management that facilitates seamless sharing of product data among various application programs in virtual enterprises. Three types of knowledge are managed by the knowledge management system - metadata, ontology, and mapping. In this environment, we consider both business applications (e.g., ERP, SCM, and EDI System) and engineering applications (e.g., CAD and CAM system).

• Korean Journal of Computational Design and Engineering
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• v.6 no.4
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• pp.229-235
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• 2001

As the networks (i.e., intranet and internet) proliferate all over the world, it is inevitable to move some (or all) of the enterprise activities into virtual spaces. Differently from business data, product data have complex semantics and thus are not properly exchanged among different application programs. Even though some neutral formats of product data have been developed by standard organizations, exchanging them among various application programs still needs the comprehensive understanding of the complex semantics. Recently, it is widely recognized that capturing more knowledge is the next step to overcome the current difficulties on sharing product data. In this paper, we utilize the ontology concept in order to facilitate information search far product data in the internet environment. A prototype of search system implemented using the ontology for automobile product data is presented.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.1
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• pp.29-34
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• 2016

One of the most important aspects of the research on multi-agent systems is the definition of agent communication languages(ACLs) and the specification of a proper formal semantics of ACLs. In this paper, we propose an illocutionary effect-based FIPA-ACL semantics which overcomes the two traditional semantic approaches. The key idea of this new semantics is based on the semantic concepts of success and satisfaction conditions of illocutionary acts in speech act theory, and the common ground theory-based framework. As case studies using this new semantics, we define the primitive speech acts of FIPA-ACL such as inform and request. For the strengths of the proposed approach we illustrate our new semantics on an e-commerce agent purchase negotiation. Also, we compare this approach with two traditional semantic approaches for ACLs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.2022-2042
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• 2014

The term "big data" has recently gained widespread attention in the field of information technology (IT). One of the key challenges in making use of big data lies in finding ways to uncover relevant and valuable information. The high volume, velocity, and variety of big data hinder the use of solutions that are available for smaller datasets, which involve the manual interpretation of data. Semantic computing technologies have been proposed as a means of dealing with these issues, and with the advent of linked data in recent years, have become central to mainstream semantic computing. This paper attempts to uncover the state-of-the-art semantics-based approaches and tools that can be leveraged to enrich and enhance today's big data. It presents research on the latest literature, including 61 studies from 2011 to 2014. In addition, it highlights the key challenges that semantic approaches need to address in the near future. For instance, this paper presents cutting-edge approaches to ontology engineering, ontology evolution, searching and filtering relevant information, extracting and reasoning, distributed (web-scale) reasoning, and representing big data. It also makes recommendations that may encourage researchers to more deeply explore the applications of semantic technology, which could improve the processing of big data. The findings of this study contribute to the existing body of basic knowledge on semantics and computational issues related to big data, and may trigger further research on the field. Our analysis shows that there is a need to put more effort into proposing new approaches, and that tools must be created that support researchers and practitioners in realizing the true power of semantic computing and solving the crucial issues of big data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1129-1133
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• 2006

In this thesis, we propose a semantics-based video retrieval system which supports semantics-retrieval for various users of massive video data. Proposed system automatically processes the extraction of contents information which video data has and retrieval process using agent which integrate annotation-based retrieval and feature-based retrieval. From experiment, the designed and implemented system shows increase of recall rate and precision rate for video data scene retrieval in performance assessment.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.863-868
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• 2005

Hardware and software codesign framework called PeaCE(Ptolemy extension as a Codesign Environment) was developed. It allows to express both data flow and control flow which is described as fFSM which extends traditional finite state machine. While the fFSM model provides lots of syntactic constructs for describing control flow, it has a lack of their formality and then difficulties in verifying the specification. In order to define the formal semantics of the fFSM, in this paper, firstly the hierarchical structure in the model is flattened and then the step semantics is defined. As a result, some important bugs such as race condition, ambiguous transition, and circulartransition can be formally detected in the model.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.587-590
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• 2002

We propose a semantics filter aimed at filtering unnecessary data for a user. In the Geographic Information Systems (GIS), transfer of spatial data for each user is one of the important problems. We design a system that filters spatial data by using user's information adaptively. Our system derives the degree of geographical knowledge and the priority of buildings by using fuzzy reasoning. Furthermore, this system computes the priority of roads by deriving the contiguity relation between a building and a road. This paper describes a method for filtering of spatial data.