• Journal of Korea Spatial Information System Society
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• v.9 no.3
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• pp.1-16
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• 2007

A spatial data warehouse is a system to support decision making using a spatial data cube. A spatial data cube is composed of a dimension table and a fact table. For decision support using this spatial data cube, the concept hierarchy of spatial dimension and the summarized information of spatial fact should be provided. In the previous researches, however, spatial summarized information is deficient. In this paper, the spatial aggregation for spatial summarized information in a spatial data warehouse is proposed. The proposed spatial aggregation is separated of both the numerical aggregation and the object aggregation. The numerical aggregation is the operation to return a numerical data as a result of spatial analysis and the object aggregation returns the result represented to object. We provide the extended struct of spatial data for spatial aggregation and so our proposed method is efficient.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.109-120
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• 2004

Since the late of 1990, there have been number of studies on the required number of probe vehicles and/or optimal aggregation interval sizes for travel time estimation and forecasting. However, in general one to five minutes are used as aggregation intervals for the travel time estimation intervals for the travel time estimation and/or forecasting of loop detector system without a reasonable validation. The objective of this study is to deveop models for identifying optimal aggregation interval sizes of loop detector data for travel time estimation and prediction. This study developed Cross Valiated Mean Square Error (CVMSE) model for the link and route travel time forecasting, The developed models were applied to the loop detector data of Kyeongbu expressway. It was found that the optimal aggregation sizes for the travel time estimation and forecasting are three to five minutes and ten to twenty minutes, respectively.

• Journal of KIISE
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• v.42 no.6
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• pp.781-790
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• 2015

In recent times, microblogs have become popular owing to the development of the Internet and mobile environments. Among the various types of microblog data, those containing location data are referred to as spatial social Web objects. General aggregations of such microblog data include data aggregation per user for a single piece of information. This study proposes a spatial aggregation algorithm that combines a general aggregation with spatial data and uses the Geohash and MapReduce operations to perform spatial social analysis, by using microblog data with the characteristics of a spatial social Web object. The proposed algorithm provides the foundation for a meaningful spatial social analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.581-590
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• 2017

This study analyzes the effect of floating population, locational characteristics and spatial autocorrelation on foodservice sales using big data provided by the Seoul Institute. Although big data provided by public sector is growing recently, research difficulties are occurred due to the difference of aggregation units of data. In this study, the aggregation unit of a dependent variable, sales of foodservice is SKT unit but those of independent variables are various, which are provided as the aggregation unit of Korea National Statistical Office, administration dong unit and point. To overcome this problem, we convert all data to the SKT aggregation unit. The spatial error model, SEM is used for analysing spatial autocorrelation. Floating population, the number of nearby workers, and the area of aggregation unit effect positively on foodservice sales. In addition, the sales of Jung-gu, Yeongdeungpo-gu and Songpa-gu are less than that of Gangnam-gu. This study provides implications for further study by showing the usefulness and limitations of converting aggregation units of heterogeneous spatial data.

• Journal of KIISE:Databases
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• v.35 no.3
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• pp.218-230
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• 2008

The temporal aggregate in temporal databases is an extension of the conventional aggregate to include the time on the range condition of aggregation. It is a useful operation for Historical Data Warehouses, Call Data Records, and so on. In this paper, we propose a structure for the temporal aggregation with multiple selection predicates, called the ITA-tree, and an aggregate processing method based on the structure. In the ITA-tree, we transform the time interval of a record into a single value, called the T-value. Then, we index records according to their T-values like a $B^+$-tree style. For possible hot-spot situations, we also propose an improvement of the ITA-tree, called the eITA-tree. Through analyses and experiments, we evaluate the performance of the proposed method.

• The KIPS Transactions:PartD
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• v.14D no.6
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• pp.597-604
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• 2007

Stream data is a continuous flow of information that mostly arrives as the form of an infinite rapid stream. Recently researchers show a great deal of interests in analyzing such data to obtain value added information. Here, we propose an efficient cube computation algorithm for multidimensional analysis of stream data. The fact that stream data arrives in an unsorted fashion and aggregation results can only be obtained after the last data item has been read. cube computation requires a tremendous amount of memory. In order to resolve such difficulties, we compute user selected aggregation fables only, and use a combination of an way and AVL trees as a temporary storage for aggregation tables. The proposed cube computation algorithm works even when main memory is not large enough to store all the aggregation tables during the computation. We showed that the proposed algorithm is practically fast enough by theoretical analysis and performance evaluation.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.43-55
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• 2005

Spatiotemporal databases support methods of recording and querying for spatiotemporal data to user by offering both spatial management and historical information on various types of objects in the real world. We can answer to the following query in real world: 'What is the average of volume of pesticide sprayed for cach farm land from April to August on 2001, within some query window' Such aggregation queries have both temporal and spatial constraint. However, previous works for aggregation are attached only to temporal aggregation or spatial aggregation. So they have problems that are difficult to apply for spatiotemporal data directly which have both spatial and temporal constraint. Therefore, in this paper, we propose spatiotemporal aggregate functions for analysis of spatiotemporal data which have spatiotemporal characteristic, such as stCOUNT, stSUM, stAVG, stMAX, stMIN. We also show that our proposal resulted in the convenience and improvement of query in application systems, and facility of analysis on spatiotemporal data which the previous temporal or spatial aggregate functions are not able to analyze, by applying to the estate management system. Then, we show the validity of our algorithm performance through the evaluation of spatiotemporal aggregate functions.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.1503-1506
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• 2003

시공간 데이터베이스는 실세계에 존재하는 다양한 유형의 객체에 대한 공간 관리와 이력정보를 동시에 제공함으로써 사용자에게 시공간 데이터에 대한 저장 및 질의 수단을 제공한다. 질의 연산 중 집계 연산은 특정한 조건을 만족하는 데이터에 대하여 계산을 수행한 결과 값을 반환하는 연산으로, 다양한 분야에서 데이터의 분석을 위해 사용된다. 그러나 기존의 집계에 대한 연구는 시간 또는 공간에만 편중되어 시간과 공간 제약을 모두 가진 실세계의 응용에 직접 적용할 수 없다. 따라서 이 논문에서는 실세계 응용들의 분석을 위한 시공간 집계함수를 제안하고, 실제 응용에서의 분석을 위한 질의 예를 보인다. 제안된 시공간 집계함수에 의해 사용자는 응용시스템에 따른 시공간데이터 분석을 위해 간략하고 편리한 질의 할 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.172-174
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• 2005

센서 네트워크에서 집계(aggregation) 연산은 센서 네트워크를 데이터베이스로 구현하는데 있어서 중요하게 제공되어져야 하는 서비스이다 현재 연구되고 있는 것으로 집계 연산을 센서 네트워크의 특징상으로 분류하여 근접한 결과값을 받는 것을 허용하고 집계 값을 자식노드가 부모노드로 보내는 기간을 부모노드가 자식노드에게 나누어 할당하여 센서 네트워크상에 적절히 구현하는 것에 대해 알아보고 집계 그루핑을 하는 과정에서 데이터웨어하우징 연구의 최신기술인 점진적인 덜 관리 기법을 통해 센서노드들의 평균값에 대해 새로운 값이 추가될 때 다시 모든 값을 계산하기 않고 변경된 값만 적용하여 계산함으로 좀더 에너지 효율적으로 확장하는 것을 제안하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.143-147
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• 2011

집단급식사업을 할 때 재료의 신선한 공급을 위한 신속성, 음식의 매출액과 재료비, 인건비, 경비 등의 관련비용 집계에 대한 정확성과 기업회계 결산에 대한 어려움이 있다. 집단급식사업은 통신과 컴퓨터를 이용하여 유통 ERP를 구축하고, 사업장을 여러 군데로 확장하여 정확한 정보의 집계와 전달에 관한 연구가 필요하다. 본 논문에서는 집단급식사업의 유통 ERP를 연구하고, 구축 운영하여 급식 매출과 원가의 요소를 집계한다. 또한 집단급식사업장 단위의 매출액에 대한 재료비, 인건비, 경비 등 요소를 집계하고, 급식 자재의 유통을 위한 구매 발주와 낙찰된 식자재의 계약과 결과 값으로 예측 Simulation하여 본다. 집단급식 사업장 단위에서 마감되면 시도 단위와 전국 단위의 자산 및 손익 계산을 하는 ERP를 연구한다. 본 논문 연구를 통하여 집단급식사업의 ERP 발전과 물류 유통 산업 발전에 기여하게 될 것이다.