• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.319-324
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• 2018

In this paper, we designed and implemented a code conversion method between ISO/IEC 10646 and the multi-byte code set. The Universal Multiple-Octet Coded Character Set(UCS) provides codes for more than 65,000 characters, huge increase over ASCII's code capacity of 128 characters. It is applicable to the representation, transmission, interchange, processing, storage, input and presentation of the written form of the language throughout the world. Therefore, it is so important to guide on code conversion methods to their customers during customer systems are migrated to the environment which the UCS code system is used and/or the current code systems, i.e., ASCII PC code and EBCDIC host code, are used with the UCS together. Code conversion utility including the mapping table between the UCS and IBM new host code is shown for the purpose of the explanation of code conversion algorithm and its implementation in the system. The programs are successfully executed in the real system environments and so can be delivered to the customer during its migration stage from the UCS to the current IBM code system and vice versa.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.31-45
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• 2005

In this paper, convert in RDF triple and a RDF document through RDF document converters and design metadata schema about a digital camcorder after use Wrapper technology, and acquiring commodity information of a HTML page about the digital camcorder which these papers are defined so as to be different by electronic commerce stores, and is expressed. Save in digital camcorder domain ontology storage that implemented to relational database to DCC knowledge base ontology as convert to OWL Web ontology based on designed metadata schema. Through compare with rdf and DCCKBO, mapping, and inference process, provide to buyers by DCC information of the store that had the commodity purchasing information which is the best, and proposed a dynamic Web ontology guessed to contents of the best commodity purchasing information, and to define domain ontology saved in DCCKBO.

• The Journal of Society for e-Business Studies
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• v.19 no.3
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• pp.107-123
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• 2014

Current text mining techniques suffer from the problem that the conventional text representation models cannot express the semantic or conceptual information for the textual documents written with natural languages. The conventional text models represent the textual documents as bag of words, which include vector space model, Boolean model, statistical model, and tensor space model. These models express documents only with the term literals for indexing and the frequency-based weights for their corresponding terms; that is, they ignore semantical information, sequential order information, and structural information of terms. Most of the text mining techniques have been developed assuming that the given documents are represented as 'bag-of-words' based text models. However, currently, confronting the big data era, a new paradigm of text representation model is required which can analyse huge amounts of textual documents more precisely. Our text model regards the 'concept' as an independent space equated with the 'term' and 'document' spaces used in the vector space model, and it expresses the relatedness among the three spaces. To develop the concept space, we use Wikipedia data, each of which defines a single concept. Consequently, a document collection is represented as a 3-order tensor with semantic information, and then the proposed model is called text cuboid model in our paper. Through experiments using the popular 20NewsGroup document corpus, we prove the superiority of the proposed text model in terms of document clustering and concept clustering.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.1-10
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• 2020

National R & D data covers information in all fields from basic science research to industrialization, but it is expressed in technical terms, which make it difficult for the public to use. Accordingly, NTIS developed and launched the data curation service 'R&D issue service', which selects national R&D information on national and social issues and provides them to the public. Therefore, this study aims to analyze the effect of a data curation service on NTIS users' access to R&D data and suggest how to develop the curation service. The R&D issue service extracts issue from the news article and provide related national R&D projects, achievements and major research institute. All raw data used for the service are open to the public, organized in a report format and provided as PDF files. In addition, automative process is developed for all NTIS users to make individual issue packaging like administrator. The results show that 'R&D issue service' launching increases users' access and convenience to R&D data related to major issues, and the number of page views of users increased after the service was opened.

• The Journal of Society for e-Business Studies
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• v.9 no.4
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• pp.117-136
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• 2004

As the time-to-market gets more important for competitiveness of an enterprise in manufacturing industry, it becomes important to shorten the development cycle of a product. Reuse of existing design models and e-Catalog for components are required for faster product development. To achieve this goal, an electric catalog must provide parametric CAD models since parametric information is indispensable for configuration design. There are difficulties in building up a parametric library of all the necessary combination using a CAD system, since we have too many combinations of components for a product. For example, there are at least 80 million combinations of components on one page of paper catalog of a mold base. To solve this problem, we propose the method of table parametric for the automatic generation of parametric CAD models. Any combination of mold base can be generated by mapping between a classification system of an electric catalog and the design parameters set of the table parametric. We propose how to select parametric models and to construct the design parameters set.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.473-483
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• 2020

This paper proposes a tourism recommendation system in intelligent cloud environment using information of tourist behavior applied with perceived value. This proposed system applied tourist information and empirical analysis information that reflected the perceptual value of tourists in their behavior to the tourism recommendation system using wide and deep learning technology. This proposal system was applied to the tourism recommendation system by collecting and analyzing various tourist information that can be collected and analyzing the values that tourists were usually aware of and the intentions of people's behavior. It provides empirical information by analyzing and mapping the association of tourism information, perceived value and behavior to tourism platforms in various fields that have been used. In addition, the tourism recommendation system using wide and deep learning technology, which can achieve both memorization and generalization in one model by learning linear model components and neural only components together, and the method of pipeline operation was presented. As a result of applying wide and deep learning model, the recommendation system presented in this paper showed that the app subscription rate on the visiting page of the tourism-related app store increased by 3.9% compared to the control group, and the other 1% group applied a model using only the same variables and only the deep side of the neural network structure, resulting in a 1% increase in subscription rate compared to the model using only the deep side. In addition, by measuring the area (AUC) below the receiver operating characteristic curve for the dataset, offline AUC was also derived that the wide-and-deep learning model was somewhat higher, but more influential in online traffic.