• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.285-290
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• 2009

An association rule mining has been studied to find hidden data pattern in data mining. A realization of fast processing method have became a big issue because it treated a great number of transaction data. The time which is derived by association rule finding method geometrically increase according to a number of item included data. Accordingly, the process to reduce the number of rules is necessarily needed. We propose the T-algorithm that is efficient rule reduction algorithm. The T-algorithm can reduce effectively the number of association rules. Because that the T-algorithm compares transaction data item with binary format. And improves a support and a confidence between items. The performance of the proposed T-algorithm is evaluated from a simulation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.291-294
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• 2013

연관 규칙 감축 기법은 대규모 데이터를 사용하는 Socially aware computing분야에서 매우 중요한 이슈이다. 본 논문에서는 수집된 각종 데이터들을 각 속성 기준에 따라 이진 변환한 후 가중치를 부여하고 논리식 감축 방법을 이용하여 신뢰성을 보장하는 규칙을 도출하는 새로운 데이터 감축 기법을 제안한다. 이는 컴퓨터 시뮬레이션 결과 기존의 방식들에 비해 지지도, 신뢰도, 규칙 감소율, 연관 규칙 추출 시간에 좋은 성능을 보였으며 이는 빠른 시간 내에 신뢰성 높은 대규모 데이터 처리가 필요한 Socially aware computing분야에 적합하다고 판단한다.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.501-510
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• 2002

During drought or impending drought period, the reservoir operation method is required to incorporate demand-management policy rule. The objective of this study is focused to the development of demand reduction rule by incorporating hedging-effect for a single reservoir system. To improve the performance measure of the objective function and constraints, we could incorporate three risk performance criteria proposed by Hashimoto et al. (1982) by mixed-integer programming and also incorporate successive linear programming to overcome nonlinear hedging term from the previous study(Shih et al., 1994). To verify this model, this hedging rule was applied to the Daechung multi-purpose dam. As a result, we could evaluate optimal hedging parameters and monthly trigger volumes.

• Environmental and Resource Economics Review
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• v.20 no.2
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• pp.167-198
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• 2011

The Korean government recently announced greenhouse gases (GHG) emissions reduction target as 30% of 2020 business as usual (BAU) emission projection. As carbon emissions trading is widely used to achieve reductions in the emissions of pollutants, this study deals with the sectoral allocation of initial carbon emission permits in Korea. This research tests the effectiveness of a variety of allocation rules based on the bankruptcy problem in cooperative game theory and hybrid input-output tables which combines environmental statistics with input-output tables. The impact of initial emission permits allocation on economic growth is also analyzed through green growth accounting. According to the analysis result, annual GDP growth rate of Korea is expected to be 4.03%, 4.23%, and 3.67% under Proportional, Constrained Equal Awards, and Constrained Equal Losses rules, respectively. These rates are approximately from 0.69% points to 0.13% points lower than the growth rate of 4.36% without compulsory $CO_2$ reduction. Thus, CEA rule is the most favorable in terms of GDP growth. This study confirms the importance of industry level study on the carbon reduction plan and initial carbon emission permits should reflect the characteristic of each industry.

• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.365-377
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• 2006

Proteins are known to perform a biological function by interacting with other proteins or compounds. Since protein interaction is intrinsic to most cellular processes, prediction of protein interaction is an important issue in post-genomic biology where abundant interaction data have been produced by many research groups. In this paper, we present an associative feature mining method to predict implicit protein-protein interactions of Saccharomyces cerevisiae from public protein interaction data. We discretized continuous-valued features by maximal interdependence-based discretization approach. We also employed feature dimension reduction filter (FDRF) method which is based on the information theory to select optimal informative features, to boost prediction accuracy and overall mining speed, and to overcome the dimensionality problem of conventional data mining approaches. We used association rule discovery algorithm for associative feature and rule mining to predict protein interaction. Using the discovered associative feature we predicted implicit protein interactions which have not been observed in training data. According to the experimental results, the proposed method accomplished about 96.5% prediction accuracy with reduced computation time which is about 29.4% faster than conventional method with no feature filter in association rule mining.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.13-24
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• 2015

Customer complaints handling helps organizations to retain existing customers and attract new customers, as well. As Voice of the Customer (VOC) is one of the main sources of customer complaints, many organizations utilize VOC to enhance customer satisfaction. Effective management of VOC has been proved as one of the best ways to maintain organization's brand image and reputation. In spite of its importance, little has been reported on the utilization of VOC to detect faults in a telecommunication industry. In this paper, association rule mining based on VOC is used to identify root fault causes of a telecommunications network. To do that, VOC of a Communication Service Provider has been collected first. Then, association rule mining has also been conducted with various support and confidence levels. As a result, root fault causes of the telecommunications network can be identified. It is expected that this study can be used as a basis for decisions about customer satisfaction management such as preventive maintenances or reduction of the customer maintenance cost.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1563-1566
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• 2008

본 논문에서는 데이터의 전처리과정으로 SNMP MIB 데이터에 대한 속성 부분집합의 선택 방법(attribute subset selection)을 사용하여 특징선택 및 축소(feature selection & reduction)를 실시하였다. 또한 데이터 마이닝의 대표적인 해석학적 분석 모델인 연관관계규칙기법(association rule mining)을 이용하여 트래픽 폭주 공격 및 공격유형별 SNMP MIB 데이터에 내재되어 있는 특징들을 규칙의 형태로 추출하여 분석하는 의미론적 심층해석을 실시하였다. 공격유형에 대한 패턴 규칙의 추출 및 분석은 공격이 발생한 프로토콜에 대해서만 서비스를 제한하고 관리할 수 있는 정책적 근거를 제공함으로써 보다 안정적인 네트워크 환경과 원활한 자원관리를 지원할 수 있다. 본 논문에서 제시한 트래픽 폭주 공격 및 공격유형별 데이터로부터의 자동적 특징의 규칙 추출 및 의미론적 해석방법은 침입탐지 시스템을 위한 새로운 방법론에 모멘텀을 제시할 수 있다는 긍정적인 가능성과 함께 침입탐지 및 대응시스템의 정책 수립을 지원할 수 있을 것으로 기대된다.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.877-884
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• 2011

The decision tree is a representative algorithm of data mining and used in many domains such as retail target marketing, fraud detection, data reduction, variable screening, category merging, etc. This method is most useful in classification problems, and to make predictions for a target group after dividing it into several small groups. When we create a model of decision tree with a large number of input variables, we suffer difficulties in exploration and analysis of the model because of complex trees. And we can often find some association exist between input variables by external variables despite of no intrinsic association. In this paper, we study on the removal method of unnecessary input variables using multiple external association rules. And then we apply the removal method to actual data for its efficiencies.

• Archives of Craniofacial Surgery
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• v.21 no.5
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• pp.283-287
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• 2020

Background: Closed reduction is the standard treatment for nasal bone fractures, which are the most common type of facial bone fractures. We investigated the effect of closed reduction on quality of life. Methods: The 15-dimensional health-related quality of life survey was administered to 120 patients who underwent closed reduction under general anesthesia for nasal bone fractures from February 2018 to December 2019, on both the day after surgery and 3 months after surgery. Three months postoperatively, the presence or absence of five nasal symptoms (nose obstruction, snoring, pain, nasal secretions, and aesthetic dissatisfaction) was also evaluated. Results: The quality of life items that showed significant changes between immediately after surgery and 3 months postoperatively were breathing, sleeping, speech, excretion, and discomfort. Low scores were found at 3 months for breathing, sleeping, and distress. There were 31 patients (25.83%) with nose obstruction, 25 (20.83%) with snoring, 12 (10.00%), with pain, 11 (9.17%) with nasal secretions, and 29 (24.17%) with aesthetic dissatisfaction. Conclusion: Closed reduction affected patients' quality of life, although most aspects improved significantly after 3 months. However, it was not possible to rule out deterioration of quality of life due to complications and dissatisfaction after surgery.

• Journal of Information Technology Applications and Management
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• v.11 no.2
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• pp.227-237
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• 2004

While the WWW offers an incredibly rich base of information, organized as a hypertext, it does not provide a uniform and efficient way to retrieve specific information. When one tries to find information entering several query terms into a search engine, the highly-ranked pages in the result usually contain many irrelevant or useless pages. The problem is that single-term queries do not contain sufficient information to specify exactly which web pages are needed by the user. The purpose of this paper is to describe the employment of association rules in data mining for developing networks and computing associative coefficient among the terms. And this paper shows how the dynamic query expansion and/or reduction can be performed in information retrieval.