• Title/Summary/Keyword: 연관 규칙 탐사

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Visual Exploration based Approach for Extracting the Interesting Association Rules (유용한 연관 규칙 추출을 위한 시각적 탐색 기반 접근법)

  • Kim, Jun-Woo;Kang, Hyun-Kyung
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.9
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    • pp.177-187
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    • 2013
  • Association rule mining is a popular data mining technique with a wide range of application domains, and aims to extract the cause-and-effect relations between the discrete items included in transaction data. However, analysts sometimes have trouble in interpreting and using the plethora of association rules extracted from a large amount of data. To address this problem, this paper aims to propose a novel approach called HTM for extracting the interesting association rules from given transaction data. The HTM approach consists of three main steps, hierarchical clustering, table-view, and mosaic plot, and each step provides the analysts with appropriate visual representation. For illustration, we applied our approach for analyzing the mass health examination data, and the result of this experiment reveals that the HTM approach help the analysts to find the interesting association rules in more effective way.

Deriving Local Association Rules by User Segmentation (사용자 구분에 의한 지역적 연관규칙의 유도)

  • Park, Se-Il;Lee, Soo-Wun
    • Journal of KIISE:Software and Applications
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    • v.29 no.1_2
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    • pp.53-64
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    • 2002
  • Association rule discovery is a method that detects associative relationships between items or attributes in transactions. It is one of the most widely studied problems in data mining because it offers useful insight into the types of dependencies that exist in a data set. However, most studies on association rule discovery have the drawback that they can not discover association rules among user groups that have common characteristics. To solve this problem, we segment the set of users into user-subgroups by using feature selection and the user segmentation, thus local association rules in user-subgroup can be discovered. To evaluate that the local association rules are more appropriated than the global association rules in each user-subgroup, derived local association rules are compared with global association rules in terms of several evaluation measures.

Design and Implementation of A Data Mining System for One-to-One Marketing in EC Merchant Systems (전자상거래 머천트 시스템에서의 원투원 마케팅을 위한 데이터마이닝 시스템의 설계 및 구현)

  • 김종달;홍정희;김성민;남도원;이동하;김성훈;이전영
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10a
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    • pp.117-119
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    • 1999
  • 전자상거래에서 판매 실적을 높이기 위한 효과적인 방법의 하나는 사용자에 따라 개별화된 정보의 제공, 즉 원투원 마케팅의 개념을 도입하는 것이다. 이를 위해서는 사용자의 구매 성향이나 사용자의 특성에 대한 지식베이스가 있어야 한다. 이러한 지식베이스로 데이터마이닝 기법중의 하나인 연관규칙을 도입하였다. 본 논문에서는 연관규칙을 기본 연산으로 하는 데이터마이닝 시스템의 설계와 구현을 기술하였다. 사용자와 제품간의 연관규칙을 추출하여 동적으로 제공되는 웹 문서를 생성하는데 필요한 지식베이스를 구축하였다. 또한 구축된 데이터마이닝 시스템은 연관규칙 탐사 엔진과 개념 계층 관리기로 구성되어 있으며, 대용량의 데이터를 다루기 위해 기존의 방법과는 다른 파일을 기반으로 한 빈번항목집합 인덱싱 기법을 제시하였다.

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Mining Association Rule on Service Data using Frequency and Weight (빈발도와 가중치를 이용한 서비스 연관 규칙 마이닝)

  • Hwang, Jeong Hee
    • Journal of Digital Contents Society
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    • v.17 no.2
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    • pp.81-88
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    • 2016
  • The general frequent pattern mining considers frequency and support of items. To extract useful information, it is necessary to consider frequency and weight of items that reflects the changing of user interest as time passes. The suitable services considering time or location is requested by user so that the weighted mining method is necessary. We propose a method of weighted frequent pattern mining based on service ontology. The weight considering time and location is given to service items and it is applied to association rule mining method. The extracted rule is combined with stored service rule and it is based on timely service to offer for user.

An Efficient Algorithm for Mining Ranged Association Rules (영역 연관규칙 탐사를 위한 효율적 알고리즘)

  • 조일래
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.1 no.2
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    • pp.169-181
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    • 1997
  • Some association rules can have very high confidence in a sub-interval or a subrange of the domain, though not quite high confidence in the whole domain. In this paper, we define a ranged association rule, an association with high confidence worthy of special attention in a sub-domain, and further propose an efficient algorithm which finds out ranged association rules. The proposed algorithm is data-driven method in a sense that hypothetical subranges are built based on data distribution itself. In addition, to avoid redundant database scanning, we devise an effective in-memory data structure, that is collected through single database scanning. The simulation shows that the suggested algorithm has reliable performance at the acceptable time cost in actual application areas.

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Analysis on Relation between Rehabilitation Training Movement and Muscle Activation using Weighted Association Rule Discovery (가중연관규칙 탐사를 이용한 재활훈련운동과 근육 활성의 연관성 분석)

  • Lee, Ah-Reum;Piao, Youn-Jun;Kwon, Tae-Kyu;Kim, Jung-Ja
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.6
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    • pp.7-17
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    • 2009
  • The precise analysis of exercise data for designing an effective rehabilitation system is very important as a feedback for planing the next exercising step. Many subjective and reliable research outcomes that were obtained by analysis and evaluation for the human motor ability by various methods of biomechanical experiments have been introduced. Most of them include quantitative analysis based on basic statistical methods, which are not practical enough for application to real clinical problems. In this situation, data mining technology can be a promising approach for clinical decision support system by discovering meaningful hidden rules and patterns from large volume of data obtained from the problem domain. In this research, in order to find relational rules between posture training type and muscle activation pattern, we investigated an application of the WAR(Weishted Association Rule) to the biomechanical data obtained mainly for evaluation of postural control ability. The discovered rules can be used as a quantitative prior knowledge for expert's decision making for rehabilitation plan. The discovered rules can be used as a more qualitative and useful priori knowledge for the rehabilitation and clinical expert's decision-making, and as a index for planning an optimal rehabilitation exercise model for a patient.

A Method for Predicting Effect based on the Causal relations of Interval Events (인터벌이벤트의 인과관계에 기초한 영향력 예측 기법)

  • Song, Myung-Jin;Kim, Dae-In;Hwang, Bu-Hyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.11a
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    • pp.793-794
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    • 2009
  • 이벤트 사이에 존재하는 연관 정보를 탐사함으로서 발생 가능한 이벤트를 예측할 수 있다. 그러나 기존의 시간 데이터마이닝 기법은 어느 정도 영향을 주고받았는지에 대한 영향력은 예측할 수 없다. 본 논문에서는 인터벌이벤트 사이에 존재하는 연관 정보를 탐사하고 탐사된 규칙에 대한 영향력을 측정할 수 있는 방법을 제안한다. 제안 방법은 이벤트 지속성을 고려하여 인터벌이벤트를 구성하고 빈발 이벤트 사이에 존재하는 연관 정보에 대한 영향력 정도를 측정한다. 그리고 이벤트 발생에 대한 주요한 원인이벤트를 탐사함으로서 이벤트 인과관계에 대한 다양한 정보를 제공할 수 있다.

An Efficient Algorithm For Mining Association Rules In Main Memory Systems (대용량 주기억장치 시스템에서 효율적인 연관 규칙 탐사 알고리즘)

  • Lee, Jae-Mun
    • The KIPS Transactions:PartD
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    • v.9D no.4
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    • pp.579-586
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    • 2002
  • This paper propose an efficient algorithm for mining association rules in the large main memory systems. To do this, the paper attempts firstly to extend the conventional algorithms such as DHP and Partition in order to be compatible to the large main memory systems and proposes secondly an algorithm to improve Partition algorithm by applying the techniques of the hash table and the bit map. The proposed algorithm is compared to the extended DHP within the experimental environments and the results show up to 65% performance improvement in comparison to the expanded DHP.

Web document prediction using forward reference path traversal patterns (전 방향 참조 경로 탐사 패턴을 이용한 웹 문서 예측)

  • 김양규;손기락
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10b
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    • pp.112-114
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    • 2004
  • 오늘날 웹을 이용하는 사용자들의 웹 검색 형태를 저장한 웹 로그 데이터들은 데이터 마이닝을 위한 중요한 자료가 되고 있다. 이들 웹 로그들로부터 사용자의 현재 행동을 기반으로 사용자가 다음에 요청할 요구를 예측할 수 있는 예측 모델을 만들 수 있다. 하지만 이들 웹 로그들은 크기가 매우 크고 분석하기가 어렵다. 이런 문제를 해결하기 위해 이미 않은 방법이 제안되었다. 그 중에서 효과적으로 예측할 수 있도록 제안된 순차적 분류 기반에 연관법칙을 적용한 예측 기법이 있다. 본 논문에서는 전방향 참조 경로 탐사 패턴 알고리즘을 적용하여 연관규칙에 기반 한 웹 문서 예측 기법을 향상시키는 모델을 제안한다.

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Association Service Mining using Level Cross Tree (레벨 교차 트리를 이용한 연관 서비스 탐사)

  • Hwang, Jeong Hee
    • Journal of Digital Contents Society
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    • v.15 no.5
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    • pp.569-577
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    • 2014
  • The various services are required to user in time and space. It is important to provide suitable service to user according to user's circumstance. Therefore it is need to provide services to user through mining by latest information of user activity and service history. In this paper we propose a mining method to search association rule using service history based on spatiotemporal information and service ontology. In this method, we find the associative service pattern using level-cross tree on service ontology. The proposed method is to be a basic research to find the service pattern to provide high quality service to user according to season, location and age under the same context.