• Journal of the Korean Geographical Society
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• v.47 no.1
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• pp.140-157
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• 2012

Most of global citizens in the globalization era want to live peacefully in the symbiotic relationship among each region or locality with its identity. From this perspective, the new regionalist models of development such as new industrial districts, industrial clusters, regional innovation systems, and global city-regions isn't helpful to most of regions because they were developed to increase the global competitiveness of industrial region from a few advanced industrial areas. This study attempts to develop 'regional differential development' as an alternative regional development theory. This theory puts emphasis on the truth that the difference or differential industry between regions in the real world connotes two essential values of development like the symbiosis of global citizens and the regional identity. Regional differential development seeks the development of regional differential industry on the basis of geographical elements with differential advantage, and hence it reviews significantly geographical elements including location, natural environment(landform, soil, climate, etc.), natural resources, population, transportation, culture, and landscape which appear substantially differently among regions. And to realize regional differential development successfully, it is crucial that actors(government, company, related institutions, and regional residents) actively participate and play each complementary role in the relationship of cooperation and conflict. Further study needs to secure the universal validity of this theory through many empirical studies.

• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.893-914
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• 2016

This paper describes the development of an inquiry-based fieldwork program based on Yangdong village where students explore the ways that it can develop in a sustainable way. Important considerations in an inquiry-based fieldwork design include what the key inquiry questions should be, the geographical issues of fieldwork location, the potential roles of mobile technologies, design of learning activities and a final product, and the roles of a teacher. Student fieldwork activities, including mapping land-use changes at the building level, detecting what should be changed or remain the same, and conducting interview with residents to examine their perceptions of overall tourism impacts, are supported by mobile technologies (i.e., the Collector for ArcGIS and the Google Forms). Twenty one high school students participated in a field test of the program in February 2016, which allowed authors to evaluate the program. Students' pre-, in-, and post-fieldwork activities were observed and the data and final products which they gathered and producted were analyzed. The post-program survey indicated that the students deepened and expanded their understanding of Yangdong village and expressed their satisfaction with the program in general. Incorporating mobile technologies into inquiry-based geographical fieldwork can help students involved in collaborative problem solving and creative activities in real world settings and create a shareable multimodal product combining maps, photo, and text.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.173-193
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component-based software development to promote application interaction and integration within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web services repositories not only be well-structured but also provide efficient tools for an environment supporting reusable software components for both service providers and consumers. As the potential of Web services for service-oriented computing is becoming widely recognized, the demand for an integrated framework that facilitates service discovery and publishing is concomitantly growing. In our research, we propose a framework that facilitates Web service discovery and publishing by combining clustering techniques and leveraging the semantics of the XML-based service specification in WSDL files. We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the Web service domain. We have developed a Web service discovery tool based on the proposed approach using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web services repositories. We believe that both service providers and consumers in a service-oriented computing environment can benefit from our Web service discovery approach.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.1-10
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• 2013

Personalization aims to provide customized contents to each user by using the user's personal preferences. In this sense, the core parts of personalization are regarded as recommendation technologies, which can recommend the proper contents or products to each user according to his/her preference. Prior studies have proposed novel recommendation technologies because they recognized the importance of recommender systems. Among several recommendation technologies, collaborative filtering (CF) has been actively studied and applied in real-world applications. The CF, however, often suffers sparsity or scalability problems. Prior research also recognized the importance of these two problems and therefore proposed many solutions. Many prior studies, however, suffered from problems, such as requiring additional time and cost for solving the limitations by utilizing additional information from other sources besides the existing user-item matrix. This study proposes a novel implicit rating approach for collaborative filtering in order to mitigate the sparsity problem as well as to enhance the performance of recommender systems. In this study, we propose the methods of reducing the sparsity problem through supplementing the user-item matrix based on the implicit rating approach, which measures the trust level among users via the existing user-item matrix. This study provides the preliminary experimental results for testing the usefulness of the proposed model.

• Journal of Navigation and Port Research
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• v.41 no.4
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• pp.215-228
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• 2017

Taking a look at recent trends of port cities, many port cities in the world have been shedding new light on the function being kept by existing port spaces, caused by changes of industrial structure according to the stream of the times, developments of surrounding areas, and etc., and we can see that its meaning also has been changing. However, in case of domestic port spaces they are in the real situation not responding to those movements quickly. Therefore, unlike the existing zoning system dividing functionally urban spaces according to use simply, in this study FBCs getting the timelight recently as a system capable of reflecting spatial characteristics at the maximum have been utilized as a measure for solving current problems of urban spaces. The purpose of this study is to propose the direction of urban planning approach that harmonizes the whole harbor space by strengthening the interlinkage between heterogeneous spaces of port area and port area using FBCs. FBCs are institutional devices that are proposed and implemented in the United States to reflect the unique characteristics of the space, that is, the location and the uniqueness, and the pedestrian-oriented space planning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.278-281
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• 2018

The early Web technology was to show text information through a browser. However, as web technology advances, it is possible to show large amounts of multimedia data through browsers. Web technologies are being applied in a variety of fields such as sensor network, hardware control, and data collection and analysis for big data and AI services. As a result, the standard has been prepared for the Internet of Things, which typically controls a sensor via HTTP communication and provides information to users, by installing a web browser on the interface of the Internet of Things. In addition, the recent development of web-assembly enabled 3D objects, virtual/enhancing real-world content that could not be run in web browsers through a native language of C-class. Factors that evaluate the performance of existing Web applications include performance, network resources, and security. However, since there are many areas in which web applications are applied, it is time to revisit and review these factors. In this thesis, we will conduct an analysis of the factors that assess the performance of a web application. We intend to establish an indicator of the development of web-based applications by reviewing the analysis of each element, its main points, and its needs to be supplemented.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.643-652
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• 2006

Decision trees are mainly used for the classification and prediction in data mining. The distribution of spatial data and relationships with their neighborhoods are very important when conducting classification for spatial data mining in the real world. Spatial decision trees in previous works have been designed for reflecting spatial data characteristic by rating Euclidean distance. But it only explains the distance of objects in spatial dimension so that it is hard to represent the distribution of spatial data and their relationships. This paper proposes a decision tree based on spatial entropy that represents the distribution of spatial data with the dispersion and dissimilarity. The dispersion presents the distribution of spatial objects within the belonged class. And dissimilarity indicates the distribution and its relationship with other classes. The rate of dispersion by dissimilarity presents that how related spatial distribution and classified data with non-spatial attributes we. Our experiment evaluates accuracy and building time of a decision tree as compared to previous methods. We achieve an improvement in performance by about 18%, 11%, respectively.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.485-494
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• 2008

Huge amounts of various web items such as keywords, images, and web pages are being made widely available on the Web. The popularities of such web items continuously change over time, and mining temporal patterns in popularities of web items is an important problem that is useful for several web applications. For example, the temporal patterns in popularities of search keywords help web search enterprises predict future popular keywords, enabling them to make price decisions when marketing search keywords to advertisers. However, presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in popularities of web items. We treat the popularities of web items as time-series, and propose gapmeasure to quantify the similarity between the popularities of two web items. To reduce the computation overhead for this measure, an efficient method using the Fast Fourier Transform (FFT) is presented. We assume that the popularities of web items are not necessarily following any probabilistic distribution or periodic. For finding clusters of web items with similar popularity trends, we propose to use a density-based clustering algorithm based on the gap measure. Our experiments using the popularity trends of search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.535-542
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• 2013

Since case-based reasoning(CBR) has many advantages, it has been used for supporting decision making in various areas including medical checkup, production planning, customer classification, and so on. However, there are several factors to be set by heuristics when designing effective CBR systems. Among these factors, this study addresses the issue of selecting appropriate neighbors in case retrieval step. As the criterion for selecting appropriate neighbors, conventional studies have used the preset number of neighbors to combine(i.e. k of k-nearest neighbor), or the relative portion of the maximum similarity. However, this study proposes to use the absolute similarity threshold varying from 0 to 1, as the criterion for selecting appropriate neighbors to combine. In this case, too small similarity threshold value may make the model rarely produce the solution. To avoid this, we propose to adopt the coverage, which implies the ratio of the cases in which solutions are produced over the total number of the training cases, and to set it as the constraint when optimizing the similarity threshold. To validate the usefulness of the proposed model, we applied it to a real-world target marketing case of an online shopping mall in Korea. As a result, we found that the proposed model might significantly improve the performance of CBR.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2007.11a
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• pp.109-113
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• 2007

This paper introduces a system, Simulation based Stochastic Markup Estimation System (S2ME), for estimating optimum markup for a project. The system was designed and implemented to better represent the real world system involved in construction bidding. The findings obtained from the analysis of existing assumptions used in the previous quantitative markup estimation methods were incorporated to improve the accuracy and predictability of the S2ME. The existing methods has four categories of assumption as follows; (1) The number of competitors and who is the competitors are known, (2) A typical competitor, who is fictitious, is assumed for easy computation, (3) the ratio of bid price against cost estimate (B/C) is assumed to follow normal distribution, (4) The deterministic output obtained from the probabilistic equation of existing models is assumed to be acceptable. However, these assumptions compromise the accuracy of prediction. In practice, the bidding patterns of the bidders are randomized in competitive bidding. To complement the lack of accuracy contributed by these assumptions, bidding project was randomly selected from the pool of bidding database in the simulation experiment. The probability to win the bid in the competitive bidding was computed using the profile of the competitors appeared in the selected bidding project record. The expected profit and probability to win the bid was calculated by selecting a bidding record randomly in an iteration of the simulation experiment under the assumption that the bidding pattern retained in historical bidding DB manifest revival. The existing computation, which is handled by means of deterministic procedure, were converted into stochastic model using simulation modeling and analysis technique as follows; (1) estimating the probability distribution functions of competitors' B/C which were obtained from historical bidding DB, (2) analyzing the sensitivity against the increment of markup using normal distribution and actual probability distribution estimated by distribution fitting, (3) estimating the maximum expected profit and optimum markup range. In the case study, the best fitted probability distribution function was estimated using the historical bidding DB retaining the competitors' bidding behavior so that the reliability was improved by estimating the output obtained from simulation experiment.