• Title/Summary/Keyword: Relation rule

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Target Marketing using Inverse Association Rule (역 연관규칙을 이용한 타겟 마케팅)

  • 황준현;김재련
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2002.11a
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    • pp.241-249
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    • 2002
  • Making traditional plan of target marketing based on Association Rule has brought restriction to obtain the target of marketing. This paper is to present Inverse Association Rule as a new association rule for target marketing. Inverse Association Rule does not use information about relation between items that customers purchase like Association Rule, but use information about relation between items that customers do not pruchase. By adding Inverse Association Rule to target marketing, we generate new marketing rule to look for new target of marketing. From new marketing rule, this paper is to show direct marketing about target item and indirect marketing about another item associated with target item to sell target item. The reason is that sales of the item associated with target item have an influence on sales of target item.

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Relation for the Measure of Association and the Criteria of Association Rule in Ordinal Database

  • Park, Hee-Chang;Lee, Ho-Soon
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.2
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    • pp.207-216
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    • 2005
  • One of the well-studied problems in data mining is the search for association rules. Association rules are useful for determining correlations between attributes of a relation and have applications in marketing, financial and retail sectors. There are three criteria of association rule; support, confidence, lift. The goal of association rule mining is to find all the rules with support and confidence exceeding some user specified thresholds. We can know there is association between two items by the criteria of association rules. But we can not know the degree of association between two items. In this paper we examine the relation between the measures of association and the criteria of association rule for ordinal data.

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The Excess and Deficit Rule and The Rule of False Position (동양의 영부족술과 서양의 가정법)

  • Chang Hyewon
    • Journal for History of Mathematics
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    • v.18 no.1
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    • pp.33-48
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    • 2005
  • The Rule of False Position is known as an arithmetical solution of algebraical equations. On the other hand, the Excess-Deficit Rule is an algorithm for calculating about excessive or deficient quantitative relations, which is found in the ancient eastern mathematical books, including the nine chapters on the mathematical arts. It is usually said that the origin of the Rule of False Position is the Excess-Deficit Rule in ancient Chinese mathematics. In relation to these facts, we pose two questions: - As many authors explain, the excess-deficit rule is a solution of simultaneous linear equations? - Which relation is there between the two rules explicitly? To answer these Questions, we consider the Rule of Single/Double False Position and research the Excess-Deficit Rule in some ancient mathematical books of Chosun Dynasty that was heavily affected by Chinese mathematics. And we pursue their historical traces in Egypt, Arab and Europe. As a result, we can make sure of the status of the Excess-Deficit Rule differing from the Rectangular Arrays(the solution of simultaneous linear equations) and identify the relation of the two rules: the application of the Excess-Deficit Rule including supposition in ancient Chinese mathematics corresponds to the Rule of Double False Position in western mathematics. In addition, we try to appreciate didactical value of the Rule of False Position which is apt to be considered as a historical by-product.

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Relation for the Measure of Association and the Criteria of Association Rule in Ordinal Database

  • Park, Hee-Chang;Lee, Ho-Soon
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.10a
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    • pp.197-213
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    • 2003
  • One of the well-studied problems in data mining is the search for association rules. The goal of association rule mining is to find all the rules with support and confidence exceeding some user specified thresholds. In this paper we consider the relation between the measure of association and the criteria of association rule for ordinal data.

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Pipe Support Modeling & Fabrication Drawing Generation on GSCAD (Pipe Support Modeling 및 제작도 작성 GSCAD 적용 사례)

  • Min, Byung-Cheon;Park, Jung-Hyun;Kang, Young-Min;Kim, Eun-Sub
    • Special Issue of the Society of Naval Architects of Korea
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    • 2009.09a
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    • pp.40-46
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    • 2009
  • The GSCAD (Global Shipbuilding CAD) System used in Samsung Heavy Industries is based on the Relation and Rule. The design area where excellence of these Relation & Rule can be used fully is pipe support modeling. That's because, many rules are required to place a pipe support and it's supported by hull structural object. Samsung Heavy Industries has been customizing the Relation and Rule supported by SmarMarine3d(R) to model pipe support easily and satisfies standard. Also, the pipe support fabrication drawing program was developed to generate a drawing for the pipe support customized. This paper reviews the characteristics of pipe support modeling on GSCAD and the Rules customized also, fabrication drawing program will be introduced.

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Criteria of Association Rule based on Chi-Square for Nominal Database

  • Park, Hee-Chang;Lee, Ho-Soon
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.04a
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    • pp.25-38
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    • 2004
  • Association rule mining searches for interesting relationships among items in a given database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. In this paper we present the relation between the measure of association based on chi square statistic and the criteria of association rule for nominal database and propose the objective criteria for association.

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Exploration of Association Rules for Social Survey Data

  • Park, Hee-Chang;Cho, Kwang-Hyun
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.04a
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    • pp.18-24
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    • 2005
  • The methods of data mining are decision tree, association rules, clustering, neural network and so on. Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. We analyze Gyeongnam social indicator survey data by 2003 using association rule technique for environment information. Association rules are useful for determining correlations between attributes of a relation and have applications in marketing, financial and retail sectors. We can use association rule outputs in environmental preservation and environmental improvement.

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Rule-Based Filler on Misidentification of Vision Sensor for Robot Knowledge Instantiation (Vision Sensor를 사용하는 로봇지식 관리를 위한 Rule 기반의 인식 오류 검출 필터)

  • Lee, Dae-Sic;Lim, Gi-Hyun;Suh, Il-Hong
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.349-350
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    • 2008
  • 지능 로봇은 표현 가능한 사물, 공간을 모델링하기 위해 주변 환경을 인지하고, 자신이 수행할 수 있는 행동을 결합하여 임무를 수행하게 된다. 이를 위해 온톨로지를 사용하여 사물, 공간, 상황 및 행동을 표현하고 특정 임무 수행을 위한 자바 기반 Rule을 통해 다양한 추론 방법을 제공하는 로봇 지식 체계를 사용하였다. 사용된 로봇 지식 체계는 생성되는 인스턴스가 자료의 클래스와 속성 값이 일관성 있고 다른 자료와 모순되지 않음을 보장해 준다. 이러한 로봇 지식 체계를 효율적으로 사용하기 위해서는 완전한 온톨로지 인스턴스의 생성이 밑받침 되어야 한다. 하지만 실제 환경에서 로봇이 Vision Sensor를 통해 사물을 인식할 때 False Positive False Negative와 같은 인식 오류를 발생시키는 문제점이 있다. 이를 보완 하기 위해 본 논문에서는 물체와 물체간의 Spatial Relation, Temporal Relation과 각 물체마다의 인식률 및 속성을 고려하여 물체 인식 오류에서도 안정적으로 인스턴스 관리를 가능하게 하는 Rule 기반의 일식오류 검출 필터를 제안한다.

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A study on insignificant rules discovery in association rule mining (연관성규칙에서 의미 없는 규칙의 발견에 관한 연구)

  • Cho, Kwang-Hyun;Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.1
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    • pp.81-88
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    • 2011
  • Association rule mining searches for interesting relationships among items in a given database. There are three primary quality measures for association rule, support and confidence and lift. In order to improve the efficiency of existing mining algorithms, constraints were applied during the mining process to generate only those association rules that are interesting to users instead of all the association rules. When we create relation rule, we can often find a lot of rules. This can find rule that direct relativity by intervening variable does not exist. In this study we try to discovery an insignificant rule in association rules by intervening variable. Result of this study can understand relativity about rule that is created in relation rule more exactly.

Target Marketing using Inverse Association Rule (역 연관규칙을 이용한 타겟 마케팅)

  • 황준현;김재련
    • Journal of Intelligence and Information Systems
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    • v.9 no.1
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    • pp.195-209
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    • 2003
  • Making traditional plan of target marketing based on association rule has brought restriction to obtain the target of marketing. This paper is to present inverse association rule as a new association rule for target marketing. Inverse association rule does not use information about relation between items that customers purchase, but use information about relation between items that customers do not purchase. By adding inverse association rule to target marketing, we generate new marketing strategy to look for new target of marketing. There are three steps to apply the marketing strategy proposed by this Paper to target marketing. Firstly, a database is converted to an inverse database. Although inverse association rules can be generated from a database, it is easier to explain inverse association rule in an inverse database than in a database. Secondly, association rules and inverse association rules are generated from inverse database. Finally, two types of rules which are created in the previous steps are applied to target marketing. From new marketing rule, this paper is to show direct marketing about target item and indirect marketing about another item associated with target item to sell target item. The reason is that sales of the item associated with target item have an influence on sales of target item.

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