• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.967-974
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• 2004

An OLAP system is the decision support tool with which a user can analyze the information interactively in the various aspects. However, the traditional existing construction of an OLAP system has the inefficiency problem of increasing the time and cost caused by the frequent changes of the users requirements. In this paper, we analyse existing construction procedure of OLAP systems and propose a prototyping OLAP View based on the star schema which can help and guide the designer In supporting efficiently of users requirements. Through an implementation of S shopping mall using the OLAP View, we show that our proposal is able to support OLAP construction strategy and provide accurate understanding of data resources. With an OLAP View, we can reduce the required time and cost of implementing OLAP system.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.971-980
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• 2002

As the importance of knowledge management is being recognized, there is a significant amount of increase for interest in data warehousing. On-Line Analytical Processing (OLAP) systems can effectively make use of data warehouses. Although there are many commercial OLAP products, they have been developed without any kind of standard resulting in poor data exchange and difficulty in interfacing among the OLAP products. In this paper we propose an OLAP metadata interchange model that can be used among different OLAP products and have implemented an OLAP metadata interchange system that can interchange the cubes created from the metadata. XML is used for the OLAP metadata model and the user interface is Web-based, which makes it easier to interchange metadata among different OLAP products. Users can experience the different analysis environments of different products without the need to learn the complex cube creation process for each product. By extending this research to design a common query language that can be used among OLAP products, OLAP products should be able to more easily talk to one another.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.909-920
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• 2003

Nowadays, IT for CRM has been growing and developed rapidly. Typical techniques are statistical analysis tools, on-line multidimensional analytical processing (OLAP) tools, and data mining algorithms (such neural networks, decision trees, and association rules). Among customer data, web log data is very important and to use these data efficiently, applying OLAP technology to analyze multi-dimensionally. To make OLAP cube, we have to precalculate multidimensional summary results in order to get fast response. But as the number of dimensions and sparse cells increases, data explosion occurs seriously and the performance of OLAP decreases. In this paper, we presented why the web log data sparsity occurs and then what kinds of sparsity patterns generate in the two and t.he three dimensions for OLAP. Based on this research, we set up the multidimensional data models and query models for benchmark with each sparsity patterns. Finally, we evaluated the performance of three OLAP systems (MS SQL 2000 Analysis Service, Oracle Express and C-MOLAP).

• Korean Journal of Computational Design and Engineering
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• v.19 no.2
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• pp.103-110
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• 2014

Engineering changes are indispensable engineering and management activities for manufactures to develop competitive products and to maintain consistency of its product data. Analysis of engineering changes provides a core functionality to support decision makings for engineering change management. This study aims to develop a method for analysis of engineering changes based on On-Line Analytical Processing (OLAP), a proven database analysis technology that has been applied to various business areas. This approach automates data processing for engineering change analysis from product databases that follow an international standard for product data management (PDM), and enables analysts to analyze various aspects of engineering changes with its OLAP operations. The study consists of modeling a standard PDM database and a multidimensional data model for engineering change analysis, implementing the standard and multidimensional models with PDM and data cube systems and applying the implemented data cube to core functions of engineering change management, the evaluation and propagation of engineering changes.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.179-189
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• 2007

Every purchase a customer makes builds patterns about how products are purchased together. The process of finding these patterns, called market basket analysis, is composed of two steps in the Microsoft Association Algorithm. The first step is to find frequent item-sets. The second step which requires much less time than the first step does is to generate association rules based on frequent item-sets. Even though the first step, finding frequent item-sets, is the core part of market basket analysis, when applied to Online Analytical Processing(OLAP) cubes it always raises several points such as longitudinal analysis becomes impossible and many unpractical transactions are built up. In this paper, a new OLAP cube structures designing method which makes longitudinal analysis be possible and also makes only real customers' purchase patterns be identified is proposed for market basket analysis.

• The KIPS Transactions:PartC
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• v.19C no.2
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• pp.91-98
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• 2012

OLAP(On-Line Analytical Processing) is a tool to satisfy the requirements of managing overflowing data analysis. OLAP can provide an interactive analytical processing environment to every end-user. Security policy is necessary to secure sensitive data of organization according to users direct access database. But earlier studies only handled the subject in its functional aspects such as MDX(Multidimensional Expressions) and XMLA(XML for Analysis). This research work is purported for solving such problems by designing and implementing an efficient data access control mechanism for the information security on OLAP. Experimental evaluation result is proposed and its efficiency and accuracy are verified through it.

• Asia pacific journal of information systems
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• v.15 no.4
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• pp.153-164
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• 2005

Nowadays, large amounts of XML documents are available in the Internet. Thus, we need to analyze them multidimensionally in the same way as relational data. In this paper, we propose a new framework for multidimensional analysis of XML documents, which we call XML-OLAP. We base XML-OLAP on XML warehouses where all fact and dimension data are stored as XML documents. We build XML cubes from XML warehouses. We propose a new OLAP language for XML cubes, which we call XML-MDX. XML-MDX statements target XML cubes and use XQuery expressions to designate measure, axis and slicer. They incorporate text mining operations for aggregating text data. We apply XML-OLAP to the United States patent XML warehouse to demonstrate multidimensional analysis of XML documents.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.58-60
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• 2001

하루에도 수십 수백 메가 바이트까지 증가하는 웹 로그 데이터를 이용하여 실시간에 다차원분석을 가능하게 하기 위해서는 OLAP의 적용이 필요하다. 하지만 OLAP을 적용하는데 있어서 빠른 응답시간을 얻기 위해 사전처리(Precomputation)를 수행 할 시 심각한 데이터의 희박성으로 인해 데이터 폭발 현상이 발생된다. 본 논문에서는 실제 웹 로그 데이터를 사용하여 OLAP적용 시 희박성을 일으키는 원인들을 밝히고, 2, 3 차원에서의 희박성 형태를 분석함으로써 웹 로그 데이터의 희박성 처리 방식 및 성능평가에 기반이 되게 한다.

• The KIPS Transactions:PartD
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• v.12D no.7 s.103
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• pp.985-992
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• 2005

An OLAP system is a decision support tool with which a user can analyze the information interactively in the various aspects. Applying CBD(Component-based Development), which treats software as components, to implement an OLAP system has limitation in the flexibility and reusability. To overcome those limitations, we propose a method of CBD(template-based CBD) which integrates the concept of template and CBD. Through the implementation of an OLAP system with the proposed TCBD, we show that our proposal is more efficient in flexibility and reusability than CBD and decreases the period of time for the development, test, and debug.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.306-311
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• 2007

Proper management of construction productivity is one of the main drivers of project success. This research focuses on the development of a construction productivity analysis system based on Web and OLAP in order to effectively manage construction productivity. Throughout the research effort, a construction productivity analysis system was modeled using IDEFO & ERD techniques and was deployed on the WWW(World Wide Web). Based on the system modeling, this research studies the methodology for system development of construction productivity that can consult the decision of managers on job site.