• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.1
• /
• pp.451-458
• /
• 2011

In order to provide the optimal location based services such as the optimal moving path search or the scheduling pattern prediction, the extraction of significant moving pattern which is considered the temporal and spatial properties of the location-based historical data of the moving objects is essential. In this paper, for the extraction of significant moving pattern we propose the location generalization method which translates the location attributes of moving object into the spatial scope information based on $R^*$-tree for more efficient patterning the continuous changes of the location of moving objects and for indexing to the 2-dimensional spatial scope. The proposed method generates the moving sequences which is satisfied the constraints of the time interval between the spatial scopes using the generalized spatial data, and extracts the significant moving patterns using them. And it can be an efficient method for the temporal pattern mining or the analysis of moving transition of the moving objects to provide the optimal location based services.

• Spatial Information Research
• /
• v.12 no.2
• /
• pp.211-228
• /
• 2004

The purpose of this study is to analyze the sales area of gas stations to see the quality and the efficiencies of spatial distribution structure for petroleum products in Tae-jeon City. Location pattern of gas station is classified by factors of competitive facilities, transportation, population and landuse in Tae-jeon City. As a result, High profit pattern and low profit pattern is classified. The characteristics of the distribution pattern of gas station are that the while densely populated has a small sales area, the thinly populated region has huge ones. Location-allocation model is used in order to minimize the travel distance from consumer location to gas station and balance the spatial distribution of gas station in case studies. The result reveals that the model-based locations of gas stations are more dispersed and balanced in the whole Tae-jeon City compared with the actual location of gas stations. This study shows the characteristics and spatial distribution patterns of sales area and location in petroleum products distribution facilities.

• The Korean Journal of Applied Statistics
• /
• v.19 no.3
• /
• pp.599-617
• /
• 2006

Recently many LBS(Location Based Service) systems are issued in mobile computing systems. Spatial-Temporal Moving Sequence Pattern Mining is a new mining method that mines user moving patterns from user moving path histories in a sensor network environment. The frequent pattern mining is related to the items which customers buy. But on the other hand, our mining method concerns users' moving sequence paths. In this paper, we consider the sequence of moving paths so we handle the repetition of moving paths. Also, we consider the duration that user spends on the location. We proposed new Apriori_msp based on the Apriori algorithm and evaluated its performance results.

• Journal of KIISE:Databases
• /
• v.29 no.5
• /
• pp.335-346
• /
• 2002

LBS(Location Based Services) provide the location-based information to its mobile users. The primary functionality of these services is to provide useful information to its users at a minimum cost of resources. The functionality can be implemented through data mining techniques. However, conventional data mining researches have not been considered spatial and temporal aspects of data simultaneously. Therefore, these techniques are inappropriate to apply on the objects of LBS, which change spatial attributes over time. In this paper, we propose a new data mining technique for identifying the temporal patterns from the series of the locations of moving objects that have both temporal and spatial dimension. We use a spatial operation of contains to generalize the location of moving point and apply time constraints between the locations of a moving object to make a valid moving sequence. Finally, the spatio-temporal technique proposed in this paper is very practical approach in not only providing more useful knowledge to LBS, but also improving the quality of the services.

• Journal of the Korean Geographical Society
• /
• v.45 no.4
• /
• pp.521-539
• /
• 2010

Recently many local governments have carried out dong merger and abolition process to cope with rapidly changing administrative demand and environment. This administrative effort impacts substantially the locational characteristics of the existing dong offices which directly involve in the quality of local community life. In this paper, we attempt to analyze the location pattern of current dong community service centers (formerly, 'dong office') and suggest the optimal locations maximizing spatial accessibility. As an application, we examine the location pattern of the existing dong community service centers in Mapo-gu, Seoul. Moreover, we compare current spatial configurations with the optimally selected locations such as, a Median maximizing spatial efficiency, a Center maximizing spatial equity, and a Centdian exploring compromising solutions regarding the tradeoff between efficiency and equity. The analytical results present that each of dong community service centers was systematically evaluated in terms of spatial efficiency and equity and in general the community service center locations are not spatially optimized with respect to efficiency and equity, compared with the optimal locations.

• Spatial Information Research
• /
• v.5 no.1
• /
• pp.11-26
• /
• 1997

The purpose of this study is to analyze the locational characteristics of bank branch offices in Kangnam-Gu, Seoul by using Geographic Information System. The number of bank branch offices have sharply increased due to financial liberalization, while the scale of them is getting smaller. The procedure of this research has four steps. First, the spatial distribution of bank branch offices in Seoul is analyzed by the places and time. Second, the spatial variations of bank offices in dong districts of Seoul is explained by factor analysis and multiple regression analysis. Third, the location-allocation model which is embedded within network module in Arc/Info is applied in order to find out optimal location of bank offices in Kangnam-Gu. Finally, the grid module is used in creating the potential surface map for locational sites of new bank branch offices The factors to affect the location of the bank offices contain mainly economic variables including local tax, collUl1ercial area, total establismnent and total employment. The actual locational pattern of bank offices is similar to the idealized locational pattern proposed by the function of min-distance in location-allocation models. In conclusion, this study shows that spatial analysis functions may potentially be improved using GIS technologies. However in order to analyze the location of bank offices more precisely, it should be found out the way to collect more appropriate data, construct computerized base maps, and investigate consumer behaviour and behavioural characteristics of bank themselves..

• The KIPS Transactions:PartD
• /
• v.10D no.7
• /
• pp.1103-1114
• /
• 2003

Currently, one of the most critical issues in developing the service support system for various spatio-temporal applications is the discoverying of meaningful knowledge from the large volume of moving object data. This sort of knowledge refers to the spatiotemporal moving pattern. To discovery such knowledge, various relationships between moving objects such as temporal, spatial and spatiotemporal topological relationships needs to be considered in knowledge discovery. In this paper, we proposed an efficient method, MPMine, for discoverying spatiotemporal moving patterns. The method not only has considered both temporal constraint and spatial constrain but also performs the spatial generalization using a spatial topological operation, contain(). Different from the previous temporal pattern methods, the proposed method is able to save the search space by using the location summarization and generalization of the moving object data. Therefore, Efficient discoverying of the useful moving patterns is possible.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.2 s.46
• /
• pp.231-242
• /
• 2007

The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.

• Journal of Korea Spatial Information System Society
• /
• v.10 no.2
• /
• pp.63-79
• /
• 2008

With the recent development of advanced GIS and complex spatial analysis technologies, the more sophisticated technologies are being required to support the advanced knowledge for solving geographical or spatial problems in various decision support systems. In addition, necessity for research on scientific crime investigation and forensic science is increasing particularly at law enforcement agencies and investigation institutions for efficient investigation and the prevention of crimes. There are active researches on geographic profiling to predict the base location such as criminals' residence by analyzing the spatial patterns of serial crimes. However, as previous researches on geographic profiling use simply statistical methods for spatial pattern analysis and do not apply a variety of spatial and temporal analysis technologies on serial crimes, they have the low prediction accuracy. Therefore, this paper identifies the typology the spatio-temporal patterns of serial crimes according to spatial distribution of crime sites and temporal distribution on occurrence of crimes and proposes STA-BLP(Spatio-Temporal Analysis based Base Location Prediction) algorithm which predicts the base location of serial crimes more accurately based on the patterns. STA-BLP improves the prediction accuracy by considering of the anisotropic pattern of serial crimes committed by criminals who prefer specific directions on a crime trip and the learning effect of criminals through repeated movement along the same route. In addition, it can predict base location more accurately in the serial crimes from multiple bases with the local prediction for some crime sites included in a cluster and the global prediction for all crime sites. Through a variety of experiments, we proved the superiority of the STA-BLP by comparing it with previous algorithms in terms of prediction accuracy.

• Journal of Korea Spatial Information System Society
• /
• v.10 no.2
• /
• pp.49-62
• /
• 2008

This paper proposes an indoor location positioning system for the image recognition based LBS. The proposed system is a vision-based location positioning system that is implemented the augmented reality by overlaying the location results with the view of the user. For implementing, the proposed system uses the pattern matching and location model to recognize user location from images taken by a wearable mobile PC with camera. In the proposed system, the system uses the pattern matching and location model for recognizing a personal location in image sequences. The system is estimated user location by the image sequence matching and marker detection methods, and is recognized user location by using the pre-defined location model. To detect marker in image sequences, the proposed system apply to the adaptive thresholding method, and by using the location model to recognize a location, the system can be obtained more accurate and efficient results. Experimental results show that the proposed system has both quality and performance to be used as an indoor location-based services(LBS) for visitors in various environments.