STUDYING INTEREST MEASURES FOR ASSOCIATION RULES THROUGH A LOGICAL MODEL

2010 ◽  
Vol 18 (01) ◽  
pp. 87-106 ◽  
Author(s):  
MIGUEL DELGADO ◽  
M. DOLORES RUIZ ◽  
DANIEL SÁNCHEZ
Keyword(s):  
Association Rules ◽  
Logic Model ◽  
Certainty Factor ◽  
Logical Model ◽  
Interestingness Measure ◽  
Logic Approach ◽  
Salient Features ◽  
General Relations ◽  
Rule Interestingness

Many papers have addressed the task of proposing a set of convenient axioms that a good rule interestingness measure should fulfil. We provide a new study of the principles proposed until now by means of the logic model proposed by Hájek et al.14 In this model association rules can be viewed as general relations of two itemsets quantified by means of a convenient quantifier.28 Moreover, we propose and justify the addition of two new principles to the three proposed by Piatetsky-Shapiro.27 We also use the logic approach for studying the relation between the different classes of quantifiers and these axioms. We define new classes of quantifiers according to the notions of strong and very strong rules, and we present a quantifier based on the certainty factor measure,317 studying its most salient features.

An Interestingness Measure and Computation Method of Association Rules Based on Frequent Itemsets Relatedness

2011 ◽  
Vol 71-78 ◽  
pp. 4039-4043
Author(s):  
Xiang Chen ◽  
Xue Feng Zhou ◽  
Yong Zhang
Keyword(s):  
Association Rules ◽  
Association Rule ◽  
Frequent Itemsets ◽  
Computation Method ◽  
Interestingness Measure ◽  
Novel Method ◽  
The Mean ◽  
Rule Interestingness ◽  
Selection Of ◽  
Actual Relationship

To address inadequacy of association rules interestingness measure method currently, we present a novel method to measure interestingness with relatedness among items in frequent itemsets. It firstly computed relatedness between frequent k-itemsets and each subset of frequent 2-itemsets, which is a linear combination of Complementarity Intensity (CI), Substitutability Intensity (SI) and Mutual Interaction (MI). The mean of relatedness of all frequent 2-itemsets subsets was regarded as relatedness of frequent k-itemsets. Finally weighted computation method of association rule interestingness was given according to principle of objective interestingness of association rule is inversely proportional to relatedness of frequent itemsets. The method can not only sort rules, but also analyze actual relationship among all items in frequent 2-itemsets, which is conductive to selection of users on rules.

scholarly journals A novel interestingness measure based on fusion model for association rules mining

2021 ◽  
Vol 336 ◽  
pp. 05009
Author(s):  
Junrui Yang ◽  
Lin Xu
Keyword(s):  
Association Rules ◽  
Negative Association ◽  
Fusion Model ◽  
Interestingness Measures ◽  
Association Rules Mining ◽  
Interestingness Measure ◽  
Advantages And Disadvantages ◽  
Measure Model ◽  
Negative Association Rules ◽  
The Difference

Aiming at the shortcomings of the traditional "support-confidence" association rules mining framework and the problems of mining negative association rules, the concept of interestingness measure is introduced. Analyzed the advantages and disadvantages of some commonly used interestingness measures at present, and combined the cosine measure on the basis of the interestingness measure model based on the difference idea, and proposed a new interestingness measure model. The interestingness measure can effectively express the relationship between the antecedent and the subsequent part of the rule. According to this model, an association rules mining algorithm based on the interestingness measure fusion model is proposed to improve the accuracy of mining. Experiments show that the algorithm has better performance and can effectively help mining positive and negative association rules.

scholarly journals Toward a Theory of Normalizing Function of Interestingness Measure of Binary Association Rules

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Armand Armand ◽  
André Totohasina ◽  
Daniel Rajaonasy Feno
Keyword(s):  
Association Rules ◽  
Quality Measures ◽  
Measures Of Association ◽  
Interestingness Measures ◽  
Association Rules Mining ◽  
Interestingness Measure ◽  
Normalization Function

Regarding the existence of more than sixty interestingness measures proposed in the literature since 1993 till today in the topics of association rules mining and facing the importance these last one, the research on normalization probabilistic quality measures of association rules has already led to many tangible results to consolidate the various existing measures in the literature. This article recommends a simple way to perform this normalization. In the interest of a unified presentation, the article offers also a new concept of normalization function as an effective tool for resolution of the problem of normalization measures that have already their own normalization functions.

Research on the Mapping Rules of Complex Inheritance Relationship from CIM to the Logic Model

2013 ◽  
Vol 734-737 ◽  
pp. 3175-3179
Author(s):  
Dan Wang ◽  
Song Zheng Zhao ◽  
Xiao Xue Hu ◽  
Yu Xi Liu ◽  
Jia Kui Zhao
Keyword(s):  
Information Model ◽  
Logic Model ◽  
Logical Model ◽  
Unique Identifier ◽  
Multiple Inheritance ◽  
Common Information ◽  
Mapping Rules ◽  
Common Information Model ◽  
Complex Inheritance

There are not a set of perfect rules as well as implementation methods to meet the demand of electric marketing business and to transform Common Information Model (CIM) into the logical model. In this paper, the complex inheritance relationship, such as the absence of multiple inheritance and the empty of parent class, is considered in CIM. This paper also focuses on the universally unique identifier IdentifiedObject class, from which most classes inherit. Moreover, based on the research about the complex inheritance relationship from CIM to the logical model, several mapping rules are introduced, which can make the transformation come true.

scholarly journals An Improved Evaluation Methodology for Mining Association Rules

Axioms ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 17
Author(s):  
Fuguang Bao ◽  
Linghao Mao ◽  
Yiling Zhu ◽  
Cancan Xiao ◽  
Chonghuan Xu
Keyword(s):  
Risk Analysis ◽  
Association Rules ◽  
Evaluation Methodology ◽  
Personalized Recommendation ◽  
Practical Application ◽  
Chi Square ◽  
Objective Criterion ◽  
Interestingness Measure ◽  
Advantages And Disadvantages ◽  
Chi Square Analysis

At present, association rules have been widely used in prediction, personalized recommendation, risk analysis and other fields. However, it has been pointed out that the traditional framework to evaluate association rules, based on Support and Confidence as measures of importance and accuracy, has several drawbacks. Some papers presented several new evaluation methods; the most typical methods are Lift, Improvement, Validity, Conviction, Chi-square analysis, etc. Here, this paper first analyzes the advantages and disadvantages of common measurement indicators of association rules and then puts forward four new measure indicators (i.e., Bi-support, Bi-lift, Bi-improvement, and Bi-confidence) based on the analysis. At last, this paper proposes a novel Bi-directional interestingness measure framework to improve the traditional one. In conclusion, the bi-directional interestingness measure framework (Bi-support and Bi-confidence framework) is superior to the traditional ones in the aspects of the objective criterion, comprehensive definition, and practical application.

An Approach to Describing Software Logic Model

2014 ◽  
Vol 989-994 ◽  
pp. 4497-4500
Author(s):  
Xiao Guang An
Keyword(s):  
Logic Model ◽  
Logical Model

This paper proposes the concept of software logical model, the basic idea and the approach of constructing the model. It describes the structure of this model, the ways of expression and the related definitions in detail. At the same time, it has also analyzed the application direction of this model. It discusses the roles playing on the aspects of research and the analysis detailedly, in which this model improves the performance of software, optimizes the structure of software and guarantees the software will run in security. Based on this model, a kind of early security warning mechanism of software is proposed.

scholarly journals A FUZZY LOGIC APPROACH FOR DRONE CAPABILITY ANALYSIS ON DISASTER RISK ASSESSMENT

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 485-489
Author(s):  
P. Zlateva ◽  
S. Hristozov ◽  
D. Velev
Keyword(s):  
Risk Assessment ◽  
Fuzzy Logic ◽  
Disaster Risk ◽  
External Input ◽  
Logic Model ◽  
Disaster Risk Assessment ◽  
Fuzzy Logic Model ◽  
Capability Analysis ◽  
Fuzzy Logic Approach ◽  
Logic Approach

<p><strong>Abstract.</strong> The paper proposes a fuzzy logic approach for drone capability analysis on disaster risk assessment. In particular, a fuzzy logic model is designed as a hierarchical system with several inputs and one output. The system inputs corresponds to the linguistic variables, describing the of levels of the external and internal input factors, which determine the capability levels of analysed drone in respect to disaster risk assessment. As external input factors are used, for example: disaster type (flood, landslide, wildfire); weather conditions (wind speed, fog, cloud cover); operational area (urban, mountain, plain), etc. As internal input factors are considered the drone characteristics such as drone type, flight performance (stall speed, turn radius, flight endurance), payload capabilities (camera resolution, accuracy, weight, sensors), etc. The fuzzy logic system output gives the level of the drone capability on disaster risk assessment in defined conditions. The model is designed in <i>Matlab</i> computer environment using Fuzzy Logic Toolbox. Several computer simulations are carried out to validate the proposed model. The designed fuzzy logic model is part of an information system for disaster risk management using drones, which is under development.</p>

NEW APPROACHES FOR DISCOVERING EXCEPTION AND ANOMALOUS RULES

2011 ◽  
Vol 19 (02) ◽  
pp. 361-399 ◽  
Author(s):  
MIGUEL DELGADO ◽  
M. DOLORES RUIZ ◽  
DANIEL SÁNCHEZ
Keyword(s):  
Association Rules ◽  
Efficient Algorithms ◽  
Unified Framework ◽  
Useful Knowledge ◽  
New Approaches ◽  
Principal Objective ◽  
New Type ◽  
Logic Approach ◽  
The Common ◽  
The Relationship

Mining association rules is a well known framework for extracting useful knowledge from databases. Despite their proven applicability there exist other approaches that also search for novel and useful information such us peculiarities, infrequent rules, exceptions or anomalous rules. The common feature of these proposals is the low support of such type of rules. So there is a necessity of finding efficient algorithms for extracting them. The principal objective of this paper is providing a unified framework for dealing with such kind of rules. In our case, we take advantage of an existing logic approach called GUHA. This model was first presented in the middle sixties by Hájek et al. and then has been developed by Rauch and others in the last decade. Following this line, this paper also offers some interesting issues. First, it provides a deep analysis of semantics and formulation of exception and anomalous rules. Second, we define the so called double rules as a new type of rules which in conjunction with exceptions and anomalies will describe in more detail the relationship between two sets of items. Third, we give new approaches for mining them and we propose an algorithm with reasonably good performance.

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