Espresso for Rule Mining

Ashmouni, Elhoussini F.; Ramadan, Rabie A.; Rashed, Ali. A.

doi:10.1016/j.procs.2014.05.465

Cited by 2 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ashmouni, Ramadan, and Rashed. [27] proposed an approach for reducing association rules in the dataset depending on the espresso algorithm for rule minimization. A drawback of the espresso-based algorithm is that the rules resulting from this algorithm are not in the optimal minimization.…”

Section: Introductionmentioning

confidence: 99%

A Logic Design-based Approach for Frequent Itemsets Mining Using LCO Algorithm

2023

IJIES

View full text Add to dashboard Cite

Frequent itemsets (FIs) mining is the main challenge in analyzing association rules since the complexity of association rule mining is determined mainly by identifying all frequent itemsets. There are many approaches to FIs mining; each approach includes many algorithms, but there is a major weakness in the logic-design-based FIs approach because there is a limited number of methods for logic circuit or expression optimization, each of which suffers from some drawbacks that are transferred to the mining process when they are utilized for this purpose. We propose LCOFI, a new algorithm for frequent itemset mining based on the LCO algorithm, in this paper. LCOA is a new algorithm for logic circuit optimization. LCOFI utilizes the suggested operations for a bipartite graph in LCOA. The proposed algorithm is simple and efficient and supports a large number of input items. It scans the transaction database only once to construct the bipartite graphs of frequent 1-itemsets and avoids the generation of candidate itemsets. It does not require complex data structures such as trees and hash tables to validate the frequency of FIs. When applied to a variety of datasets with varying characteristics, the proposed algorithm, LCOFI, outperformed the Apriori and Fp-growth algorithms in all the experiments.

show abstract

Section: Introductionmentioning

confidence: 99%

A Logic Design-based Approach for Frequent Itemsets Mining Using LCO Algorithm

2023

IJIES

View full text Add to dashboard Cite

show abstract

Experimental comparison of the effectiveness of programs for minimizing systems of Boolean functions in the class of disjunctive normal forms

Bibilo

Loginova

2022

Informatika (Minsk)

View full text Add to dashboard Cite

Objectives. Methods, algorithms and programs for solving problems of minimizing the DNF representations of Boolean functions are widely used in the design of digital systems to reduce the complexity (crystal area) of functional combinational blocks of digital systems placed into digital VLSI.The objective of the work is experimental comparison of domestic programs for minimizing Boolean functions in the DNF class included in the FLC-2 with two well-known foreign freely distributed programs for minimizing DNF known as Espresso IIC and ABC.Methods. Four sets sample of input data were used to compare the programs – there are widely known examples on which the effectiveness of the Espresso IIC program was tested and two sets of industrial examples from the practice of designing the logic circuits. Algorithms and programs for parallelization of calculations when separate functions of minimizing have been developed. Software tools for the application of joint minimization programs with separate minimization of functions are proposed.Results. The areas of preferred use and the execution time of programs for the source systems of functions (for minimization) characterized by large parameter values of dozens of arguments and functions, tens of thousands of elementary conjunctions are revealed. The efficiency of application of minimization programs for various forms of input data assignment is investigated – DNF, orthogonalized DNF, BDD (Binary Decision Diagrams) representations for systems of functions, truth tables and perfect DNF systems.Conclusion. The experimental results show the effectiveness of parallel programs – reducing the calculation time and increasing the dimensions of solved problems of separate minimization of Boolean function systems.

show abstract

Espresso for Rule Mining

Cited by 2 publications

References 11 publications

A Logic Design-based Approach for Frequent Itemsets Mining Using LCO Algorithm

A Logic Design-based Approach for Frequent Itemsets Mining Using LCO Algorithm

Experimental comparison of the effectiveness of programs for minimizing systems of Boolean functions in the class of disjunctive normal forms

Contact Info

Product

Resources

About