• Journal of the Korean Society for information Management
• /
• v.24 no.3
• /
• pp.83-92
• /
• 2007

Semantic libraries can be used for EDI messages to exchange by implementing the semantic dictionaries. This paper describes the design information of semantic libraries for the field engineers to implement the semantic dictionary using metadata. The components of semantic libraries are semantic elements, semantic units and mapping tables. The basic characteristics and design methods related implementing are proposed. Also the metadata semantic dictionaries including the components and rules are introduced.

• The KIPS Transactions:PartD
• /
• v.14D no.4 s.114
• /
• pp.389-394
• /
• 2007

This study suggests that it dynamically generates semantic Web services from Java and C++ components in order to supporting semantic Web service by using ontology. And the semantic Web should enable greater access not only to content but also to services on the Web. It needs semantic service discovery for components. So, we add ontology-based framework to Web service generation system from components. Especially, components and ontologies are transformed UML model so that it makes WSDL documents to support a generation of dynamic Web service using object modeling. The main contribution of this study is to generate web service dynamically from components and to support semantic Web environment by using ontology. In other words, this study integrates semantic Web service based on ontology and CBD method.

• The Transactions of the Korea Information Processing Society
• /
• v.3 no.6
• /
• pp.1443-1452
• /
• 1996

In this paper, we propose a semantic similarity measure for reusable software components, which aims to provide the automatic classification process of reusable to be stored in the structure of a software library, and to provide an efficient retrieval method of the software components satisfying the user's requirements. We have identified the facets to represent component characteristics by extracting information from the component descriptions written in a natural language, composed the software component identifiers from the automatically extracted terms corresponding to each facets, and stored them which the components in the nearest locations according to the semantic similarity of the classified components. In order to retrieve components satisfying user's requirements, we measured a semantic similarity between the queries and the stored components in the software library. As a result of using the semantic similarity to retrieve reusable components, we could not only retrieve the set of components satisfying user's queries. but also reduce the retrieval time of components of user's request. And we further improve the overall retrieval efficiency by assigning relevance ranking to the retrieved components according to the degree of query satisfaction.

• The Transactions of the Korea Information Processing Society
• /
• v.3 no.4
• /
• pp.855-865
• /
• 1996

In this paper, we propose a automation of the classification process for reusable software component and construction method of structured software components library. In order to efficient and automatic classification of software component, we decide the facets to represent characteristics of software component by acquiring semantic and syntactic information from software components descriptions in natural language, and compose the software component identifier or automatic extract terms corresponds to each facets. And then, in order to construct the structured software components library, we sore in the near location with software components of similar characteristic according to semantic similarity of the classified software components. As the result of applying proposed method, we can easily identify similar software components, the classification process of software components become simple, and the software components store in the structured software components library.

• Journal of the Korean Society of Costume
• /
• v.55 no.3 s.93
• /
• pp.1-18
• /
• 2005

In this study, the transition characteristics of purple series color names appearing in the clothing of the Joseon Dynasty were examined, and the associational meaning of each name were investigated through various methods. The results are as follows; First, Such characteristics as continuity, differentiation, substitution could be observed through the investigation of color names of purple-series appeared on the clothing in the Joseon Dynasty period. Secondly, the associational meaning could be subdivided into; social position symbolic meanings, usage meanings, economic meanings, and thought meanings. The social position symbolic meanings could be observed mainly in the single names which has been used since the ancient times, usage meanings could be observed in a wide variety according to the individual color names. The economic meanings could be observed by comparing the value of colored cloths and colored threads. The thought meanings were mainly related with the Confucianism. Thirdly, the associational semantic structure were established on the basis of associational meanings of purple-series color names. Individual color name on the social position symbolic semantic structure symbolizes [government official] and [servant]. Through usage semantic structure individual color names could be understood structurally according to the social position, sex distinction, wearing situation, items of clothing, and structure of clothing. Individual names on the economic semantic structure were segmented by the semantic components of the values in [high], [medium], [low] prices, kinds and quantity of dyes. The thought semantic structure could be subdivided [Confucianism] and [The Thought of Taeil] in its semantic structure.

• Phonetics and Speech Sciences
• /
• v.7 no.4
• /
• pp.49-55
• /
• 2015

It is argued in this paper that, in determining semantic similarity, Korean words should be recategorized with a focus on the semantic relation to ontology in light of cross-linguistic morphological variations. It is proposed, in particular, that Korean semantic similarity should be measured on three tracks, human judgements track, relatedness track, and cross-part-of-speech relations track. As demonstrated in Yang et al. (2015), GloVe, the unsupervised learning machine on semantic similarity, is applicable to Korean with its performance being compared with human judgement results. Based on this compatability, it was further thought that the model's performance might most likely vary with different kinds of specific relations in different languages. An attempt was made to analyze them in terms of two major Korean-specific categories involved in their lexical and cross-POS-relations. It is concluded that languages must be analyzed by varying methods so that semantic components across languages may allow varying semantic distance in the vector space models.

• Asia pacific journal of information systems
• /
• v.7 no.1
• /
• pp.85-97
• /
• 1997

This paper is concerned with knowledge representation schemes best suited for human resource management (HRM) problem domains including human resource planing, selection, placement, compensations, performance evaluation, training and labor-management relations. In order to suggest the scheme we consider two research gods. First, we evaluate and prioritize. The knowledge representation techniques of frames rules, semantic nets and predicate logic that hove been recommended to managerial domains. The combined Analytic Hierarchy Process technique is employed to combine individual judgments effectively between two different expert groups. As a result if we are to select a single knowledge representation technique, a frame representation is best for most HRM domains and to combine frames with others is another choice. Second as a strategy for knowledge representation schemes we show some examples for each damn in terms of labeled semantic nets and two types of rules derived from the semantic nets. We propose nine knowledge components as ontologies. The labeled semantic nets con provide some benefits compared with conventional one. More clearly definea node rode information maces it easy to find the ac information. In the rule sets, the variables are the node of the semantic nets. The consistency of rules is validated by the relationship of the knowledge components.

• Smart Structures and Systems
• /
• v.31 no.4
• /
• pp.325-334
• /
• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.05a
• /
• pp.1128-1135
• /
• 2003

e-Transformation of an enterprise requires the collaboration of business processes to be suited to the business participants' purpose. To realize this collaboration, business processes should be implemented as components and the system developers could be able to reuse the components for their specific purpose. The first step of this collaboration is the discovery of exact components for business processes. A dilemma, however, is the fact that there are thousands or even millions of business processes which vary from one enterprise to another. Moreover, business processes could be decomposed into multiple levels of semantics and classified into several process areas. In general, discovery of exact business processes requires understanding of widely adopted classification schemes such as CBPC, OAGIS, or SCOR. To cope with this obstacle, business process metadata should be defined and managed regardless of specific classification schemes to support effective discovery and reuse of business processes components. In this paper, a methodology to discover business process components published in different semantic levels is proposed. The proposed methodology represents the metadata of business process components as topic maps stored in a registry and utilizes the powerful features of topic maps for process discovery. TM4J, an open-source topic map engine, is modified to support concept matching and navigation. With the implemented tool, application system developers can discover and publish the business process components effectively.

• International Journal of Advanced Culture Technology
• /
• v.12 no.1
• /
• pp.227-233
• /
• 2024

This study was conducted to understand the essential structure and meaning of the experience of participating in the Jigsaw class designed to achieve the learning goals for nursing students with different basic learning abilities, and to prepare a plan for each individual to learn as a collaborator rather than a competition with each other. As a study based on Giorgi's phenomenological research method and in-depth interviews, data collection was collected from 10 study participants from December 1, 2023 to December 20, 2023. The main question used in the interview was "What impressed you after participating in Jigsaw teaching meathod?" The transcribed data were analyzed through the stages of overall recognition, classification of semantic units, transformation of semantic units into psychological expressions, and integration into general structures according to Giorgi's qualitative analysis method. As a result, a total of 89 semantic units, 35 essential psychological meanings, 13 sub-components, and 6 components were derived. The six components include 'good communication', 'difference appear in material preparation', 'easy to understand', 'finding team members who form a learning atmosphere well', 'A talkative class', and 'Unprepared team members are uncomfortable'. Based on the above results, it is expected that students in a passive position in class will become teachers themselves, take responsibility for preparing for learning, and provide useful basic data for developing programs that cooperate among students.