• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.71-93
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• 2001

Commonly to design a database system. a conceptual database has to be designed and then it is transformed into a logical database schema prior to building a target database system. This paper proposes a method which transforms a Temporal Entity-Relationship Model(TERM) into a Temporal Object-Oriented Model(TOOM) to build an efficient database schema. I formalize the time concept in view of object versioning and specify the constraints required during transformation procedure. The proposed transformation method contributes to getting the logical temporal data from the conceptual temporal events Without any loss of semantics, Compared to other approaches of supporting various properties, this approach is more general and efficient because it is the semantically seamless transformation method by using the orthogonality of types of objects, semantics of relationships and constraints over roles.

• The Journal of Society for e-Business Studies
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• v.9 no.3
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• pp.259-276
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• 2004

ebXML and Web Services provide UDDI and ebXML registry for storing and managing the business and Service information of companies, respectively. Recently, W3C have released the OWL(Web Ontology Language) to Recommendation, and OWL-S proposed to describe the semantics of Web Services using the OWL ontologies. In this paper, we compared the OWL-S with the registry information model(RIM) of ebXML and the data structure of UDDI, and directly connect ones, which that of ebXML similar to that of UDDI; we extend the structure of the OWL to connect the rests. Consequently, our system enables to construct the ontologies of services and discover their semantics by using the information stored in the registries, and tintegrate UDDI, ebXML registry and OWL-S registry. By using the extending OWL-S documents in our system, agents can utilize for the semantic matchmaking.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.461-472
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• 2005

In this paper, we design and implement a graphical bio-ontology management system based on OWL(Web Ontology Language). It allows domain experts to easily manage sophisticated bio-ontologies in which biological knowledge is encoded. The knowledge can be seamlessly modeled into the ontology by well defined graphical notations, which capture most of subtle semantics inherently existing between biological terms. Our system provides a new construction mechanism, which can determine a considerable part of relationships between terms by their inheritance and inverse-inheritance. For keeping their semantics to be consistent, the mechanism supplies domain experts with information available from relationships being constructed or already constructed. The constructed ontology is basically formatted by OWL, which may benefit from its powerful semantic expressiveness. Additionally, it can be automatically translated into other standard languages without semantic loss, such as RDF/RDFS, DAML+OIL and so on. The main characteristics of our system is that it enables domain experts to delicately model the bio-ontology by the visualized construction mechanisms adopting well-defined graphical notations based on OWL.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.483-494
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• 2001

Most of hypertext retrieval models consider documents as independent entities. They ignore relationships between documents of link semantics. in an information retrieval system for hypertext documents, retrieval effectiveness can be improved when ling information is used. Previous link-based hypertext retrieval models ignore link information while indexing. They utilize link information to re-rank the retrieval results. Therefore they are limited that only the documents is result-set utilize link information. This paper utilizes link information when indexing. We present how to use term weighting and inLinks weighting for ranking the relevant documents. Experimental results show that recall and precision evaluation according to the link semantics and the comparison with previously link_based hypertext retrieval model.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.846-858
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• 1997

Despite elaegant semantics and a lot of features, pure functional programming languages do not provide an affcient way of represnting states.Many researches have been done to resolve the problem, however, another problem arises that it is hard to implement becaese of the complex type system and redujction rule.Therefore, the scheme which simplifies the reduction rule and maintains states effciently is needed to have the implemen-taiton dffetive.This paper proposes st-calculus, the excution model of a functinal language with states and proves that the proposed model satistiies the church-Rosser theorem.It has simple reduction rules and the ability of rerpresenting states without, and the difficulties with implementation may be reduced by simplifving the reduction rules.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.406-412
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• 2022

Scene classification of very high-resolution (VHR) imagery can attribute semantics to land cover in a variety of domains. Real-world application requirements have not been addressed by conventional techniques for remote sensing image classification. Recent research has demonstrated that deep convolutional neural networks (CNNs) are effective at extracting features due to their strong feature extraction capabilities. In order to improve classification performance, these approaches rely primarily on semantic information. Since the abstract and global semantic information makes it difficult for the network to correctly classify scene images with similar structures and high interclass similarity, it achieves a low classification accuracy. We propose a VHR remote sensing image classification model that uses extracts the global feature from the original VHR image using an EfficientNet-V2L CNN pre-trained to detect similar classes. The image is then classified using a multilayer perceptron (MLP). This method was evaluated using two benchmark remote sensing datasets: the 21-class UC Merced, and the 38-class PatternNet. As compared to other state-of-the-art models, the proposed model significantly improves performance.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1665-1680
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• 1997

The Entity-Relationship (E-R) model is widely used not only to increase understanding between user and designer, but also to model the relationship of real world data appropriately when designing database system in many application areas. It should be then transformed into an Object-Oriented database model which gives good merits to represent and manipulate data efficiently. Therefore, a method of transforming an E-R model into an Object-Oriented database model should be studied, but without losing any semantics of concept for the E-R model. This paper not only deals with transformation rules taking as input the elements of E-R model and delivering the elements of an Object-Oriented database model, but also improves the concept of generalization and aggregation inheritance. The paper also presents a method of transformation of relationship depending on these rules. The proposed method that obtains Object-Oriented database schema from an E-R model with preserving the properties of the E-R model is shown with examples. The method presented is able to be used to the logical database design.

• The KIPS Transactions:PartD
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• v.12D no.1 s.97
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• pp.165-178
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• 2005

A product classification scheme is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eCl@ss, however, have a lot of limitations to meet these requirements for dynamic features of classification. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this Paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes, and describe the semantic classification model proposed in [1], which satisfies the requirements for dynamic features of product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.676-683
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• 2002

The success of XML(eXtensible Markup Language) is primarily based on its flexibility : everybody can define the structure of XML documents that represent information in the form he or she desires. XML is so flexible that XML documents cannot be automatically provided with an underlying semantics. Different tag sets, different names for elements or attributes, or different document structures in general mislead the task of classifying and clustering XML documents precisely. In this paper, we design and implement a system that allows checking the semantic-based similarity between XML tags. First, this system extracts the underlying semantics of tags and then expands the synonym set of tags using an WordNet thesaurus and user-defined word library which supports the abbreviation forms and compound words for XML tags. Seconds, considering the relative importance of XML tags in the XML documents, we extend a conventional vector space model which is the most generally used for document model in Information Retrieval field. Using this method, we have been able to check the similarity between XML tags which are represented different tags.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.95-100
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• 2009

The Semantic Web is an evolving extension of the WWW in which the semantics of information and services on the web is defined, making it possible for the web to understand and satisfy the requests of people and machines to use the web content. The sementic web relied on the ontologies that structure underling data for the purpose of comprehensive and transportable machine understanding. The Semantic Web relies on the ontologies that structure underlying data for the purpose of comprehensive and transportable machine understanding. And recommendation systems have been developed as a solution to the abundance of choice people face in many situations. This paper shows that the new recommendation method is suitable for effective recommendation on the semantic web. We present a new procedure for improving the effective recommendation by using the levelized context ontology. Our experimental results also confirm that our method has good recommendation time. Our proposed method can be generalized to fit other application domains.