• Journal of Korea Multimedia Society
• /
• v.22 no.12
• /
• pp.1466-1480
• /
• 2019

This paper addresses the efficient processing of all-farthest-neighbors (AFN) queries in spatial network databases. Given a set of data points P={p₁,p₂,…,p_|p|} in a spatial network, where the distance between two data points p and s, denoted by dist (p,s), is the length of the shortest path between them, an AFN query is defined as follows: find the farthest neighbor ω(p)∈P of each data point p such that dist(p,ω(p)) ≥ dist(p,s) for all s∈P. In this paper, we propose a shared execution algorithm called FAST (for All-Farthest-neighbors Search in spatial neTworks). Extensive experiments on real-world roadmaps confirm the efficiency and scalability of the FAST algorithm, while demonstrating a speedup of up to two orders of magnitude over a conventional solution.

• Spatial Information Research
• /
• v.21 no.1
• /
• pp.1-13
• /
• 2013

This paper describes a GIS framework for geo-semantic information retrieval in mobile computing environments. We built geographic ontologies of POI (point of interest) and weather information for use in the combination of semantic, spatial, and temporal functions in a fully integrated database. We also implemented a geo-semantic app for Android-based smartphones that can extract more appropriate POIs in terms of user contexts and geographic ontologies and can visualize the POIs using Google Maps API (application programming interface). The feasibility tests showed our geo-semantic app can provide pertinent POI information according to mobile user contexts such as location, time, schedule, and weather. We can discover a baking CVS (convenience store) in the test of bakery search and can find out a drive-in theater for a not rainy day, which are good examples of the geo-semantic query using semantic, spatial, and temporal functions. As future work, we should need ontology-based inference systems and the LOD (linked open data) of various ontologies for more advanced sharing of geographic knowledge.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.5
• /
• pp.293-302
• /
• 2019

In mountain accident events, it is important for the search team commander to determine the search area in order to secure the Golden Time. Within this period, assistance and treatment to the concerned individual will most likely prevent further injuries and harm. This paper proposes a method to determine the search priority area based on missing persons behavior and missing persons incidents statistics. GIS (Geographic Information System) and MCDM (Multi Criteria Decision Making) are integrated by applying WLC (Weighted Linear Combination) techniques. Missing persons were classified into five types, and their behavioral characteristics were analyzed to extract seven geographic analysis factors. Next, index values were set up for each missing person and element according to the behavioral characteristics, and the raster data generated by multiplying the weight of each element are superimposed to define models to select search priority areas, where each weight is calculated from the AHP (Analytical Hierarchy Process) through a pairwise comparison method obtained from search operation experts. Finally, the model generated in this study was applied to a missing person case through a virtual missing scenario, the priority area was selected, and the behavioral characteristics and topographical characteristics of the missing persons were compared with the selected area. The resulting analysis results were verified by mountain rescue experts as 'appropriate' in terms of the behavior analysis, analysis factor extraction, experimental process, and results for the missing persons.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.1851-1854
• /
• 2003

This paper suggests an algorithm which can retrieval images using correlations between the region classification of spatial image and the wavelet transform even though the images are rotated in a ${\pm}$90 degree arc. Owing to this proposed method, it was confirmed from experiments that the search about the whole image is not processed and only a few amount of informations are saved by using the mathematical statistics from the block map and transformed band which is resulted from region classification, and by performing the image search based on these, the improvement of search speed and the efficient search can be done.

• Korean Institute of Interior Design Journal
• /
• v.20 no.6
• /
• pp.36-43
• /
• 2011

The study presupposes that, ever since its modernization, the Korean local government buildings have undergone an evolutionary process of their spatial organizations and the process can be analyzed in terms of increased publicness of architectural space. For the purpose, fifteen examples of local government buildings in Korea are selected and analyzed in terms of their plans converted into spatial diagrams measuring accessibility depth. Within these analytical diagrams, some quantitative measures such as permeability and visual connection, and the number of decision making points that visitors face on the way to their targets. The study analyzes these analytic measures of selected samples which are categorized into three chronological groups in order to search any evolutionary tendency of spatial transformation. The analysis shows that the accessibility of public functions and presumably the publicness of the spatial organization of local government buildings has been increased. The results of the study implies that, to acquire architectural publicness in government buildings, not only the insertion of public programs but also the organization of open spatial structure is significant.

• The KIPS Transactions:PartD
• /
• v.10D no.7
• /
• pp.1077-1088
• /
• 2003

To increase the retrieval performance in spatial database systems, it is required to develop spatial indexing methods considered the spatial locality. The spatial locality is related to the location property of objects. The previous spatial indexing methods are not considered the circular location property that objects will be taken. In this paper, we propose a dynamic spatial index structure called $Cr^*$-tree, and evaluate the performance of the proposed index structure. This is a new spatial index structure considered the circular location property of objects in which a search space is constructed with the circular and linear domains. By the simulation results, the $Cr^*$-tree shows that the number of disk across is low and the bucket utilization is high regardless of object distribution and bucket capacity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.31 no.4
• /
• pp.259-267
• /
• 2013

GIS-based web map service is all the more accessible to the public. Among others, location query services are most frequently utilized, which are currently restricted to only one keyword search. Although there increases the demand for the service for querying multiple keywords corresponding to sequential activities(banking, having lunch, watching movie, and other activities) in various locations POI, such service is yet to be provided. The objective of the paper is to develop the k-IPS algorithm for quickly and accurately querying multiple POIs that internet users input and locating the search outcomes on a web map. The algorithm is developed by utilizing hierarchical tree structure of $R^*$-tree indexing technique to produce overlapped geometric regions. By using recursive $R^*$-tree index based spatial join process, the performance of the current spatial join operation was improved. The performance of the algorithm is tested by applying 2, 3, and 4 multiple POIs for spatial query selected from 159 keyword set. About 90% of the test outcomes are produced within 0.1 second. The algorithm proposed in this paper is expected to be utilized for providing a variety of location-based query services, of which demand increases to conveniently support for citizens' daily activities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.3
• /
• pp.339-346
• /
• 2016

Semantic search recently been used in the search field. POI is one of the most essential information that make up the geographic information, and many of the geographic information system has POI search function as a basic. In this study, we propose POI semantic search using collective intelligence. For this, we designed and implemented service that constructs empirical information from tag and image, and provides an intuitive spatial navigation experience. For POI search, collective intelligence platform that many users can participate to collect variety information was designed and implemented.

• Journal of Korea Spatial Information System Society
• /
• v.10 no.4
• /
• pp.59-66
• /
• 2008

GeoSensor network means sensor network infra and related software of specific form monitoring a variety of circumstances over geospatial. And these GeoSensor network is implemented by mixing data stream with spatial attribute, spatial relation. But, until a recent date sensor network system has been concentrated on a store and search method of sensor data stream except for a spatial information. In this paper, we propose a definition of spatial data stream and its join strategy model at GeoSensor network, which combine data stream with spatial data. Spatial data stream s defining in this paper are dynamic spatial data stream of a moving object type and static spatial data stream of a fixed type. Dynamic spatial data stream is data stream transmitted by moving sensor as GPS, while static spatial data stream is generated by joining a data stream of general sensor and a relation with location values of these sensors. This paper propose joins of dynamic spatial data stream and static spatial data stream, and cost models estimating join cost. Finally, we show verification of proposed cost models and performance by join strategy.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.3
• /
• pp.55-62
• /
• 2009

Location based Services in the ubiquitous computing environment, namely u-LBS, use very large and skewed spatial objects that are closely related to locational information. It is especially essential to achieve fast search, which is looking for POI(Point of Interest) related to the location of users. This paper examines how to search large and skewed POI efficiently in the u-LBS environment. We propose the Dynamic-level Grid based R-Tree(DGR-Tree), which is an index for point data that can reduce the cost of stationary POI search. DGR-Tree uses both R-Tree as a primary index and Dynamic-level Grid as a secondary index. DGR-Tree is optimized to be suitable for point data and solves the overlapping problem among leaf nodes. Dynamic-level Grid of DGR-Tree is created dynamically according to the density of POI. Each cell in Dynamic-level Grid has a leaf node pointer for direct access with the leaf node of the primary index. Therefore, the index access performance is improved greatly by accessing the leaf node directly through Dynamic-level Grid. We also propose a K-Nearest Neighbor(KNN) algorithm for DGR-Tree, which utilizes Dynamic-level Grid for fast access to candidate cells. The KNN algorithm for DGR-Tree provides the mechanism, which can access directly to cells enclosing given query point and adjacent cells without tree traversal. The KNN algorithm minimizes sorting cost about candidate lists with minimum distance and provides NEB(Non Extensible Boundary), which need not consider the extension of candidate nodes for KNN search.