• Korean Association of Arts Management
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• no.51
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• pp.75-102
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• 2019

This study aims to figure out the progression of Hyundai motor's corporate cultural marketing by conducting semantic network analysis. Although the previous research has focused on conception, categorization, impact, and performance of cultural marketing, they hardly pay attention to changes in cultural marketing over time. To explore the identified gap, we collected 2,315 articles concerning Hyundai motor's cultural marketing on daily newspapers printed from 2001 to 2018. The 18-year time period was classified into four periods, and lists of words were extracted and analyzed by Korean language analysis program, Textom and social network analysis program, called 'UCINET'. The outcome of our analysis indicates that Hyundai Motor's cultural marketing has been developed from the strategy of merely increasing sales to the means of distinguishing their corporate and brand identity. In the early 2000s, the words 'customer', 'The Age of Great Paintings: Rembrandt and the 17th century Dutch paintings', and 'performances' were extracted with high frequency. It shows Hyundai Motor held performance-oriented events and provided benefits to specific consumer groups under the type of 'Cultural Promotion'. In addition, as the exhibition sponsored by Hyundai motor was reported in the media with high publicity effect, the concept of 'Cultural Support' is also emerged. In the late 2000s, the top exposures were 'Seoul Arts Center' and 'Seoul Metropolitan Symphony Orchestra'. Under the concept of 'Cultural Support', both organizations and cultural events were sponsored by Hyundai motor. Hyundai Motor has the tendency to cooperate with high profile parties who have already accomplished high publicities to attract social interests and issues. In the early 2010s, Hyundai Motor created cultural marketing brand and space ('Brilliant' and 'Hyundai Art Hall') that broadened the potential target groups, which represented both 'Cultural Support' and 'Cultural Enterprise'. In the middle and late of the 2010s, as shown by the high frequency of 'brand' and 'global', Hyundai Motor has focused on the global market and viewpoint has expanded to brand building focusing on the type of 'Cultural Enterprise'.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.62-78
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• 2023

The purpose of this study is to analyze the field of Earth science at a science fair. For this purpose, 566 pieces of data spanning 21 years (2000 to 2020), acquired from entries in the Earth Science section on the science fair website, were analyzed using the semantic network method. As a result, geoscience topics have been actively explored in works submitted for the Earth Science section of the science fair. Fossils from the Cretaceous period of the Mesozoic Era were particularly predominant. Together with these, keywords corresponding to astronomy, space science, and atmospheric science formed a small-scale network. Astronomy and space science mainly dealt with the dynamic characteristics of asteroids, Venus, and Jupiter. Other subjects included the solar system, sunspots, and lunar phases. Atmospheric science has focused on atmospheric physics, atmospheric observation and analysis technology, atmospheric dynamics, air quality monitoring, while marine science has been limited to physical oceanography and geologic oceanography. This study, is expected to help select Earth Science topics and conduct inquiry activities in schools.

• Journal of Technology Innovation
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• v.21 no.1
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• pp.279-301
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• 2013

This study demonstrates how social network analysis can be used for identifying potential buyers in technology marketing; in such, the methodology and empirical results are proposed. First of all, we derived the three most important 'seed' keywords from 'technology description' sections. The technologies are generated by various types of R&D activities organized by South Korea's public research institutes in the fundamental science fields. Second, some 3, 000 words were collected from websites related to the three 'seed' keywords. Next, three network matrices (i.e., one matrix per seed keyword) were constructed. To explore the technology network structure, each network is analyzed by degree centrality and Euclidean distance. The network analysis suggests 100 potentially demanding companies and identifies seven common companies after comparing results derived from each network. The usefulness of the result is verified by investigating the business area of the firm's homepages. Finally, five out of seven firms were proven to have strong relevance to the target technology. In terms of social network analysis, this study expands its application scope of methodology by combining semantic network analysis and the technology marketing method. From a practical perspective, the empirical study suggests the illustrative framework for exploiting prospective demanding companies on the web, raising possibilities of technology commercialization in the basic research fields. Future research is planned to examine how the efficiency of process and accuracy of result is increased.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.147-150
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• 2015

본 논문에서는 고성능 컴퓨팅 시스템의 성능 향상을 위한 효율적인 동적 작업부하 균등화 정책을 제안한다. 이 정책은 시스템 자원인 CPU와 메모리를 효율적으로 사용하여 고성능 컴퓨팅 시스템의 처리량을 최대화하고, 각 작업의 수행시간을 최소화한다. 또한 이 정책은 수행중인 작업의 메모리 요구량과 각 노드의 부하 상태를 파악하여 작업을 동적으로 할당한다. 이때 작업을 할당 받은 노드가 과부하 상태가 되면 다른 노드로 작업을 이주시켜 각 노드의 작업부하를 균등하게 유지함으로써 작업의 대기시간을 줄이고, 각 작업의 수행시간을 단축한다. 본 논문에서는 시뮬레이션을 통하여 제안하는 동적 작업부하 균등화 정책이 기존의 메모리 기반의 작업부하 균등화 정책에 비해 고성능 컴퓨팅 시스템의 성능 향상 면에서 우수함을 보인다.

• Journal of Information Technology Services
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• v.9 no.1
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• pp.113-125
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• 2010

Recently, a smart space with Ubiquitous Environment is expanding rapidly due to the development of Ubiquitous Sensor Network. Therefore, more appropriate and intelligent services of the context awareness system is being required. The previous context awareness system can provide a service to the user through the inference only on the current situation. But, it does not handle certain situation properly when the system provides abnormal result. Also it does not have any proper method of generating reliable semantic data from sensed raw data. In this paper, we are trying to solve the problems as the following approaches. First, the system recognizes abnormal result and corrects it by learning feedback from the user. Second, we suggest a method of converting sensed data into more reliable semantic data. Third, we build the system based on an Ontological context model that is capable of interoperability and reusability. Therefore, the context awareness system of our study can enhance the previous system that can generate more reliable context data, can provide more effective inference method, and can provide more intelligent system structure.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.335-354
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• 2014

The accuracy of training-based activity recognition depends on the training procedure and the extent to which the training dataset comprehensively represents the activity and its varieties. Additionally, training incurs substantial cost and effort in the process of collecting training data. To address these limitations, we have developed a training-free activity recognition approach based on a fuzzy logic algorithm that utilizes a generic activity model and an associated activity semantic knowledge. The approach is validated through experimentation with real activity datasets. Results show that the fuzzy logic based algorithms exhibit comparable or better accuracy than other training-based approaches.

• Language and Information
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• v.20 no.1
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• pp.1-24
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• 2016

Korean is well-known for its topic-prominent properties. In this paper, we look into several subtypes of topic constructions whose grammatical complexities have received much attention in generative grammar. From a semantic/pragmatic view, topics in Korean can be classified into three different types: aboutness, contrastive, and scene-setting. Meanwhile, syntax can classify topic constructions into two types, depending on whether or not the comment clause following topic has a syntactic gap linked to the topic. In this paper, we review some key properties of these topic constructions in Korean, and suggest that each type is licensed by tight interactions between syntactic and semantic constraints. In particular, the paper tries to offer a Construction Grammar analysis where each grammatical component is interacting in non-modular ways and in which the multiple inheritance network of constructions plays an important role in capturing cross-cutting generalizations of the topic constructions.

• Language and Information
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• v.9 no.2
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• pp.23-48
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• 2005

This study aims to discuss the word sense distinction of Korean middle verbs for restructuring KorLexVerb 1.0. Despite the duality of its meaning and syntactic structure, the word senses of middle verb are not clearly distinguished in current dictionaries. The underspecification causes very often mismatches that a same Korean word sense is used for two different English verb senses. A close examination on the syntactic and semantic properties of middle verb shows us that the word sense distinction and the reconstruction of hierarchical structure are indispensable. Finally, by doing this fine grained word sense distinction, we propose an alternative way of classification and description of the verb polysemy for KorLexVerb 1.0 as well as for dictionary-like language resources.

• Korean Journal of Computational Design and Engineering
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• v.10 no.6
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• pp.402-411
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• 2005

Context-aware engineering services in ubiquitous environments are emerging as a viable alternative to traditional engineering services. Most of the previous approaches are computer-centered rather than human-centered. In this paper, we present a Ubiquitous and Context-Aware computing Framework for collaborative virtual Engineering $(U-CAF\acute{E})$ services. The proposed approach utilizes BPEL-based (Business Process Execution Language) process templates for engineering service orchestration and choreography and adopts semantic web-based context-awareness for providing human-centered engineering services. The paper discusses how to utilize engineering contexts and share this knowledge in support of collaborative virtual engineering services and service interfaces. The paper also discusses how Web services and JINI (Java Intelligent Network Infrastructure) services are utilized to support engineering service federations and seamless Interactions among persons, devices, and various kinds of engineering services.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.820-831
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• 2020

Extractive document summarization aims to select a few sentences while preserving its main information on a given document, but the current extractive methods do not consider the sentence-information repeat problem especially for news document summarization. In view of the importance and redundancy of news text information, in this paper, we propose a neural extractive summarization approach with joint sentence semantic clipping and selection, which can effectively solve the problem of news text summary sentence repetition. Specifically, a hierarchical selective encoding network is constructed for both sentence-level and document-level document representations, and data containing important information is extracted on news text; a sentence extractor strategy is then adopted for joint scoring and redundant information clipping. This way, our model strikes a balance between important information extraction and redundant information filtering. Experimental results on both CNN/Daily Mail dataset and Court Public Opinion News dataset we built are presented to show the effectiveness of our proposed approach in terms of ROUGE metrics, especially for redundant information filtering.