• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.429-437
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• 2022

Recently, the demand for a QA (Question Answering) system for human-machine communication has increased. Among the QA systems, a closed domain QA system that can handle spatial-related questions is called GeoQA. In this study, a new type of graph database, LPG (Labeled Property Graph) was used to overcome the limitations of the RDF (Resource Description Framework) based database, which was mainly used in the GeoQA field. In addition, GraphQL (Graph Query Language), an API-type query language, is introduced to address the fact that the LPG query language is not standardized and the GeoQA system may depend on specific products. In this study, database was built so that answers could be retrieved when spatial-related questions were entered. Each data was obtained from the national spatial information portal and local data open service. The spatial relationships between each spatial objects were calculated in advance and stored in edge form. The user's questions were first converted to GraphQL through FOL (First Order Logic) format and delivered to the database through the GraphQL server. The LPG used in the experiment is Neo4j, the graph database that currently has the highest market share, and some of the built-in functions and QGIS were used for spatial calculations. As a result of building the system, it was confirmed that the user's question could be transformed, processed through the Apollo GraphQL server, and an appropriate answer could be obtained from the database.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.587-590
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• 2002

We propose a semantics filter aimed at filtering unnecessary data for a user. In the Geographic Information Systems (GIS), transfer of spatial data for each user is one of the important problems. We design a system that filters spatial data by using user's information adaptively. Our system derives the degree of geographical knowledge and the priority of buildings by using fuzzy reasoning. Furthermore, this system computes the priority of roads by deriving the contiguity relation between a building and a road. This paper describes a method for filtering of spatial data.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.54-62
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• 2009

This paper proposes a framework for personal location based services with personal life content, for example diaries, schedules and to-do lists. A lot of Internet users are recording their personal experiences and knowledge as text and other digital media on the network. Our proposed tool provides users with an environment to store personal records with related place attributes, and to retrieve these personal records at the right place. There are two applications on this tool, a place-enhanced blog and a LBS client on a mobile phone. The place enhanced blog provides users with blog interfaces for inputting place information. The place rem inder is a browser for spatial data on the place enhanced blog. Users can generate place information by writing personal records on their blog. Furthermore, using the LBS client, other users can retrieve personal records at the appropriate spots.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1843-1854
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• 2010

The utilization of underground space has recently increased with the complication of road, the rise of the land price, and the development of green technology. Underground space ranges from classical excavations to subway, underground cities, and shopping malls where there are crowds of people. At this time, government has spent a lot of money in installing various types of safety facilities for preparations of increasing potential disasters. Therefore, an effective facility management system is required. In this paper, we propose an information retrieval process to effectively extract the facilities' information based on the ontology and spatial analysis in underground space. The ontology-based searching supports hierarchical and associated results as well as knowledge sharing with hierarchy concepts. The spatial analysis based searching has "Buffer" and "Near" functions to operate on a map without understanding any property of the facility information.

• Journal of the Korean Regional Science Association
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• v.15 no.1
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• pp.93-116
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• 1999

Recently the concept of learning has become very fashionable among academics from different economic disciplines. Economic geographers and spatial planners joined this fashion by increasingly speaking about the 'learning region'. This paper makes clear that this learning region'. This paper makes clear that this learning region concept has been launched from three angles; as spatial outcome of grand societal changes, as spatial concentration of entrepreneurial learning for innovation and as regional development concept. Despite the deficits and flaws such a young concept is faced with, such as vague definitions, the lack of empirical research and an insufficiently clear separation from existing concepts, the learning region concept might provide economic geography with more insight in agglomeration effects, stronger links with policy-making and more knowledge on path dependency and thus on unravelling the distinction between 'good' and 'bad' industrial agglomerations.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1087-1089
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• 2003

The aim of this study is to evaluate the Pi-SAR data for land cover discrimination using a standard method. For this purpose, the original polarization and Pauli components of the Pi-SAR X-band and L-band data are used and the results are compared. As a method for the land cover discrimination, the traditional method of statistical maximum likelihood decision rule is selected. To increase the accuracy of the classification result, different spatial thresholds based on local knowledge are determined and used for the actual classification process. Moreover, to reduce the speckle noise and increase the spatial homogeneity of different classes of objects, a speckle suppression filter is applied to the original Pi-SAR data before applying the classification decision rule. Overall, the research indicated that the original Pi-SAR polarization components can be successfully used for separation of different land cover types without taking taking special polarization transformations.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.525-527
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• 2003

Recently, the spatial resolution of earth observation satellites is significantly increased to a few meters. Such high spatial resolution images definitely will provide lots of information for detail-thirsty remote sensing users. However, it is more difficult to develop automated image algorithms for automated image feature extraction and pattern recognition. In this study, we propose a two-stage procedure to extract road information from high resolution satellite images. At first stage, a watershed segmentation technique is developed to classify the image into various regions. Then, a knowledge is built for road and used to extract the road regions. In this study, we use panchromatic and multi-spectral images of the IKONOS satellite as test dataset. The experiment result shows that the proposed technique can generate suitable and meaningful road objects from high spatial resolution satellite images. Apparently, misclassified regions such as parking lots are recognized as road needed further refinement in future research.

• IE interfaces
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• v.22 no.1
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• pp.17-25
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• 2009

In mobile device's user interface, menu organization is very important as well as menu structure because small display of mobile device. Menu items should be organized based on user knowledge structure to design user-centered interface. Traditionally, MDS (Multidimensional Scaling) have been most often used to expose users' perceived organization of menu items. But, information that MDS reveals is just relative spatial location of concepts and not relevant to concepts connection. Unlike MDS, Trajectory Mapping explicitly finds users' cognitive links between perceived concepts. This study proposes a Trajectory Mapping technique for eliciting knowledge structure, especially a set of cognitive pathways linking menu items, from end user. With twelve participants, MDS and Trajectory Mapping were conducted using cellular phone's menu items. And user knowledge structure was analyzed through Visual Concept Map that combination of results of MDS and Trajectory Mapping. After then, menu items were organized according to users' perceived organization. Empirical usability test was also conducted. The results of usability test showed that usability, in terms of task performance time, number of errors, and satisfaction, for newly organized interface was significantly improved compare to original interface. The methodology of this study is expected to be applicable to design a user-centered interface. In other words, Trajectory Mapping technique can be used as a design tool of user interface for imposing user knowledge structure on the interface.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.239-252
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• 2005

The major reason that spatial data warehousing has attracted a great deal of attention in business GIS in recent years is due to the wide availability of huge amount of spatial data and the imminent need for fuming such data into useful geographic information. Therefore, this research has been focused on designing and implementing the pilot tested system for spatial decision making. The purpose of the system is to predict targeted marketing area by discriminating the customers by using both transaction quantity and the number of customer using credit card in department store. Moreover, the pilot tested system of this research provides OLAP tools for interactive analysis of multidimensional data of geographically various granularities, which facilitate effective spatial data mining. focused on the analysis methodology, the case study is aiming to use GIS and clustering for knowledge discovery. Especially, the importance of this study is in the use of snowflake schema model capabilities for GIS framework.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.361-367
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• 2016

We have reported a high prevalence of breast cancer in light-polluted areas in Korea. However, it is necessary to analyze the spatial effects of light polluted areas on breast cancer because light pollution levels are correlated with region proximity to central urbanized areas in studied cities. In this study, we applied a spatial regression method (an intrinsic conditional autoregressive [iCAR] model) to analyze the relationship between the incidence of breast cancer and artificial light at night (ALAN) levels in 25 regions including central city, urbanized, and rural areas. By Poisson regression analysis, there was a significant correlation between ALAN, alcohol consumption rates, and the incidence of breast cancer. We also found significant spatial effects between ALAN and the incidence of breast cancer, with an increase in the deviance information criterion (DIC) from 374.3 to 348.6 and an increase in $R^2$ from 0.574 to 0.667. Therefore, spatial analysis (an iCAR model) is more appropriate for assessing ALAN effects on breast cancer. To our knowledge, this study is the first to show spatial effects of light pollution on breast cancer, despite the limitations of an ecological study. We suggest that a decrease in ALAN could reduce breast cancer more than expected because of spatial effects.