• IE interfaces
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• v.25 no.1
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• pp.71-78
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• 2012

Most manufacturing companies participate in various types of active collaboration to enhance competitive advantages in their arenas. In this paper, we introduce a data warehouse system that is designed for manufacturing collaboration. Just as enterprise information systems, collaboration support systems also need functions of performance measurement and monitoring. For this reason, we devise a new approach to measuring and evaluating performance of manufacturing collaboration. Specifically, we first present a concept of process warehouses for manufacturing collaboration. Next, we design a data schema of collaborative process warehouses to store and monitor collaboration performances. Finally, we implement a prototype system to support performance management of manufacturing collaboration. The proposed system can be used to effectively maintain and continuously improve collaboration in manufacturing industry.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.361-368
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• 2009

In the Urban Regeneration Project, the scale becomes huge and the composition of participating organizations is complex. It is necessary to establish the master plan fast and effectively harmonize conflict options and interests in the early stage of the project. However, the master planner, who is tasked to establish the master plan, and the master planning team, are difficult to establish the master plan fast while effectively considering various and complex information related to regeneration. The Urban Regeneration Project is composed of various types of computer files like HWP, EXL, PDF, DWG and others. When the master plan is established, it is necessary to link the information items and physical files of urban generation in order to effectively save the files in storage for easy search and utilization. This study developed a prototype system to support participating subjects of the Urban Regeneration Projects. It will effectively utilize the information items in the physical computer files using information blocks and Metadata. The developed system provides the base to effectively manage large amount of documents in the early stage of the Urban Regeneration Project and make effective decision-making using the concept of data warehouse.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.507-514
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• 2006

Various application systems are developed using RFID as a part of ubiquitous computing, and it is expected that RFID chip will become wide-spread for the distribution industry especially. Efficient and efact intelligent-type of warehouse management system is essential for small-to-medium-sized enterprises in the situation having a trouble in the viewpoint of expense and manpower. In this paper, we implement small-scale warehouse management system using log-based context awareness technology. This system is implemented to be controlled on web, configuring clients to control RFID readers and building up DBMS system in a server. Especially, it grasps user's intention of storing or delivering based on toE data for the history of user's access to the system and it reports user's irregular pattern of warehouse use and serves predictive information of the control of goods in stock. As a result, the proposed system can contribute to enhance efficiency and correctness of small-scale warehouse management.

• Spatial Information Research
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• v.11 no.2
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• pp.119-130
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• 2003

Since GIS strategic implementation plan was prepared in 1995, Seoul Metropolitan Government (SMG) has implemented the distributed GIS at department level, which prevents various SMG organizations from data-sharing and its common utilization. To solve those problems due to the fragmented GIS structure, SMG developed an action plan for the evolution of enterprise GIS with Spatial Data Warehouse (SDW). In this context, this paper initially analyzed the conceptual architecture of SDW structure and then provided the following guidelines for 1) determining the common GIS data and framework data stored at SDW to satisfy the demand for various GIS data from many SMG departments and sub-organizations, 2) developing the data synchronization process and techniques to make effective data-sharing possible, and 3) making an action plan for enterprise GIS of other self-governmental organizations.

• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.189-207
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• 1997

Recently, we have witnessed a host of emerging tools in the management support systems (MSS) area including the data warehouse/multidimensinal databases (MDDB), data mining, on-line analytical processing (OLAP), intelligent agents, World Wide Web(WWW) technologies, the Internet, and corporate intranets. These tools are reshaping MSS developments in organizations. This article reviews a set of emerging data management technologies in the knowledge discovery in databases(KDD) process and analyzes their implications for decision support. Furthermore, today's MSS are equipped with a plethora of AI techniques (artifical neural networks, and genetic algorithms, etc) fuzzy sets, modeling by example , geographical information system(GIS), logic modeling, and visual interactive modeling (VIM) , All these developments suggest that we are shifting the corporate decision making paradigm form information-driven decision making in the1980s to knowledge-driven decision making in the 1990s.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1381-1394
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• 2006

Generation methods of data cube have been studied for many years in data warehouse which supports decision making using stored data. There are two previous studies, one is multi-way array algorithm and the other is H-cubing algorithm which is based on the hyper-tree. The multi-way array algorithm stores all aggregation data in arrays, so if the base data is increased, the size of memory is also grow. The H-cubing algorithm which is based on the hyper-tree stores all tuples in one tree so the construction cost is increased. In this paper, we present an efficient data cube generation method based on hash table using weight mapping table and record hash table. Because the proposed method uses a hash table, the generation cost of data cube is decreased and the memory usage is also decreased. In the performance study, we shows that the proposed method provides faster search operation time and make data cube generation operate more efficiently.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.325-338
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• 2004

A data warehouse stores information that is collected from multiple, heterogeneous information sources for the purpose of complex querying and analysis. Information in the warehouse is typically stored In the form of materialized views, which represent pre-computed portions of frequently asked queries. One of the most important tasks of designing a warehouse is the selection of materialized views to be maintained in the warehouse. The goal is to select a set of views so that the total query response time over all queries can be minimized while a limited amount of time for maintaining the views is given(maintenance-cost view selection problem). In this paper, we propose an efficient solution to the maintenance-cost view selection problem using a genetic algorithm for computing a near-optimal set of views. Specifically, we explore the maintenance-cost view selection problem in the context of OR view graphs. We show that our approach represents a dramatic improvement in terms of time complexity over existing search-based approaches that use heuristics. Our analysis shows that the algorithm consistently yields a solution that only has an additional 10% of query cost of over the optimal query cost while at the same time exhibits an impressive performance of only a linear increase in execution time. We have implemented a prototype version of our algorithm that is used to evaluate our approach.

• Journal of Information Technology Applications and Management
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• v.12 no.1
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• pp.35-48
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• 2005

An architectural framework is developed for integrating geospatial and temporal data with relational information from which a spatio-temporal data warehouse (STDW) system is built. In order to implement the STDW, a generic conceptual model was designed that accommodated six dimensions: spatial (map object), temporal (time), agent (contractor), management (e.g. planting) and tree species (specific species) that addressed the 'where', 'when', 'who', 'what', 'why' and 'how' (5W1H) of the STDW information, respectively. A formal algebraic notation was developed based on a triplet schema that corresponded with spatial, temporal, and relational data type objects. Spatial object structures and spatial operators (spatial selection, spatial projection, and spatial join) were defined and incorporated along with other database operators having interfaces via the generic model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2453-2461
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• 2009

Faults caused by medium-voltage customers have been increased and enlarged their portion in total distribution faults even though we have done many efforts. In the previous paper, we suggested the fault prediction model and fault prevention method for these distribution line faults. However we can't directly apply this prediction model in the field. Because we don't have an useful program to predict those customers causing distribution line faults. This paper presents the construction method of data warehouse in ERP system and the program to find customers who cause distribution line faults in medium-voltage customer's electric facility management applying data mining techniques. We expect that this data warehouse and prediction program can effectively reduce faults resulted from medium-voltage customer facility.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.203-212
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• 2002

This study examined the predictive power of data mining algorithms by comparing the performance of logistic regression and decision tree algorithm, called CHAID (Chi-squared Automatic Interaction Detection), On the contrary to the previous studies, decision tree performed better than logistic regression. We have also developed a CDSS (Clinical Decision Support System) with three modules (doctor, nurse, and patient) based on data warehouse architecture. Data warehouse collects and integrates relevant information from various databases from hospital information system (HIS ). This system can help improve decision making capability of doctors and improve accessibility of educational material for patients.