• Journal of The Korean Association of Information Education
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• v.7 no.1
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• pp.113-129
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• 2003

The performance assessment is being importantly recognized and enforced in the education evaluation recently. It is not able to analyze learners synthetically because learners are assessed separately in every subjects and the other activities. On the basis of this problem, we designed and implemented the multi-dimensional processing tool. In this tool, the evaluation results of one subject area have an influence on the other related subject areas. In addition, this system helps teachers to establish and process performance assessment plan by providing all subjects database. And all of the information is processed as a whole and can be used in the counseling and school record. This system is based upon windows and can be extend to web based system later. We expect the performance assessment task can be simplified by using this system and students' ability can be assessed by various methods. This system will contribute to ensure the confidence of public education.

• Journal of the Korea Computer Industry Society
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• v.3 no.8
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• pp.1007-1018
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• 2002

A systematic and multi-dimensional analysis in evaluation results may play a role of providing both learners and instructors with essential information. Conventional types of evaluation research have a tendency of partiality for developing evaluation tools, and analyzing the evaluation results has mostly been fragmentary and a one-dimensional analysis. In this study, through analyzing evaluation results in a multi-dimensional way, a multi-dimensional evaluation result analyzing system was developed for the purpose of providing various information for both learners and instructors to accomplish quality learning teaching. Dimensions are classified into four dimensions including period, student, difficulty degree, and evaluation domain. Analysis results are presented in various types of Dcube, graphs, and spreadsheets.

• The KIPS Transactions:PartA
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• v.12A no.5 s.95
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• pp.461-470
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• 2005

In leaner-controlled environment where learners can decide and restructure the contents, methods and order of learning by themselves, it is possible to apply individualized learning in consideration of each learner's characteristics. The present study analyzed learners' learning path pattern, which is one of learners' characteristics important in Web-based teaching-learning process, using the Apriori algorithm and grouped learners according to their learning path pattern. Based on the result, we designed and implemented a multi-dimensional learning path pattern analysis system to provide individual learners with teaming paths, learning contents, learning media, supplementary teaming contents, the pattern of material presentation, etc. multi-dimensionally. According to the result of surveying satisfaction with the developed system satisfaction with supplementary learning contents was highest (Highly satisfied '$24.5\%$, Satisfied'$35.7\%$). By learners' level, satisfaction was higher in low-level learners (Highly satisfied'$20.2\%$, Satisfied'$31.2\%$) than in high-level learners (Highly satisfied'$18.4\%$, 'Satisfied'$28.54\%$). The developed system is expected to provide learners with multi-dimensionally meaningful information from various angles using OLAP technologies such as drill-up and drill-down.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.155-164
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• 2012

This study aims to identify the multidimensional variables and sub-variables and study their relative weight in music recommender systems when maximizing the rating function R. To undertake the task, a optimization formula and variables for a research model were derived from the review of prior works on recommender systems, which were then used to establish the research model for an empirical test. With the research model and the actual log data of real customers obtained from an on line music provider in Korea, multiple regression analysis was conducted to induce the optimal correlation of variables in the multidimensional model. The results showed that the correlation value against the rating function R for Items was highest, followed by Social Relations, Users and Contexts. Among sub-variables, popular music from Social Relations, genre, latest music and favourite artist from Items were high in the correlation with the rating function R. Meantime, the derived multidimensional recommender systems revealed that in a comparative analysis, it outperformed two dimensions(Users, Items) and three dimensions(Users, Items and Contexts, or Users, items and Social Relations) based recommender systems in terms of adjusted $R^2$ and the correlation of all variables against the values of the rating function R.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.999-1004
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• 2004

In this study, we identify contribution of structure-borne-noise of vehicle HVAC system using Multi-Dimensional spectral analysis (MDSA) method. Firstly, to identify the applicability of MDSA method, the case of HVAC system was modeled with four input / single output system. The four inputs which is given vibration data is composed of blower, evaporator, heater and duct. The single output is noise data from driver's seat. When the blower motor is operating, we analyze the contributions of four input / single output. As a result of experiment, we identify efficiency of systems modeled with four input / single output through ordinary coherence function (OCF) and multiple coherence function (MCF).

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.597-598
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• 2009

최근의 국가 민간의 정보시스템을 위협하는 공격들은 점점 더 복잡해지고 정교해지고 있다. 이러한 공격들에 대응하기 위하여 범국가적으로 사이버안전센터들이 설립 운영되고 있다. 그러나 이러한 대량의 정보보호 데이터를 수집 분석 대응하는 것은 여러 가지 어려움들이 존재한다. 그 문제의 본질적인 부분은 바로 방대한 데이터의 양(量)이다. 다수의 보안관제 대상 인프라들의 모든 보안데이터를 수집 하는 것은 사실상 불가능하며, 대부분의 센터들은 네트워크 접점에 중앙관리형 보안인프라를 설치함으로써 그 해결점을 찾고 있지만, 이는 최근의 나타나고 있는 다차원적인 공격에 대응하기에는 한계가 있다. 본 논문에서는 이러한 다차원 분석시스템의 기본데이터가 되는 여러 보안정보를 효과적으로 수집할 수 있는 보안정보 수집체계를 제시하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.132-134
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• 1999

통계적 공정관리(SPC)에 있어서 신속하고 정확한 공정분석은 품질과 생산성에 중대한 영향을 미치므로 정확한 공정 데이터의 수집, 빠른 데이터의 응답, 각 업무에 적당한 사용자 분석도구를 제공하는 분석하는 요구된다. 본 논문에서는 기존 SPC 환경에 WOLAP과 자바 기술을 기반으로 하여 다차원 구조로 데이터를 저장하여 빠른 분석 데이터 응답을 제공하고, 자바 애플릿 사용자 분석도구를 구현하여 사용과 관리가 용이하도록 하여 신속하고 정확한 분석과 개선 조치가 가능한 시스템을 설계하였다.

• Journal of KIISE
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• v.43 no.8
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• pp.910-918
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• 2016

A tensor is a multi-dimensional array that represents many data such as (user, user, time) in the social network system. A tensor generator is an important tool for multi-dimensional data mining research with various applications including simulation, multi-dimensional data modeling/understanding, and sampling/extrapolation. However, existing tensor generators cannot generate sparse tensors like real-world tensors that obey power law. In addition, they have limitations such as tensor sizes that can be processed and additional time required to upload generated tensor to distributed systems for further analysis. In this study, we propose TeT, a distributed tera-scale tensor generator to solve these problems. TeT generates sparse random tensor as well as sparse R-MAT and Kronecker tensor without any limitation on tensor sizes. In addition, a TeT-generated tensor is immediately ready for further tensor analysis on the same distributed system. The careful design of TeT facilitates nearly linear scalability on the number of machines.

• Digital Contents
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• no.9 s.64
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• pp.60-62
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• 1998

한국오라클은 최근 자사의 데이터 웨어하우스 솔루션을 이용해 보험개발원의 보험통계 시스템을 구축했다. 이를 통해 보험개발원은 다차원적 통계분석, 전략적 의사결정 지원 등 데이터의 전사적 관리가 가능하게 되었다. 보험개발원의 데이터 웨어하우스의 도입배경, 구축과정, 시스템 구성, 구축효과에 대해 살펴봤다.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.225-236
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• 2003

MOLAP systems store data in a multidimensional away called a 'cube' and access them using way indexes. When a cube is placed into disk, it can be Partitioned into a set of chunks of the same side length. Such a cube storage scheme is called the chunk-based MOLAP cube storage scheme. It gives data clustering effect so that all the dimensions are guaranteed to get a fair chance in terms of the query processing speed. In order to achieve high space utilization, sparse chunks are further compressed. Due to data compression, the relative position of chunks cannot be obtained in constant time without using indexes. In this paper, we propose a bitmap index for chunk-based MOLAP cubes. The index can be constructed along with the corresponding cube generation. The relative position of chunks is retained in the index so that chunk retrieval can be done in constant time. We placed in an index block as many chunks as possible so that the number of index searches is minimized for OLAP operations such as range queries. We showed the proposed index is efficient by comparing it with multidimensional indexes such as UB-tree and grid file in terms of time and space.