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Discovering interesting knowledge from a science and technology database with a genetic algorithm

Wesley Romão, Alex A. Freitas, Itana M.de S. Gimenes
2004 Applied Soft Computing  
A prototype was implemented and applied to a real-world science & technology database, containing data about the scientific production of researchers.  ...  In this context, we propose a Genetic Algorithm (GA) designed specifically to discover interesting fuzzy prediction rules.  ...  The parameters of the GA are as follows: The Data Set The application domain addressed in this paper involves a science and technology database obtained from CNPq (the Brazilian government's National  ... 
doi:10.1016/j.asoc.2003.10.002 fatcat:562rvohjyvfl5jkkxwm6q56vja

Querying Biological Sequences Docking Using Different Constraint Programming's: a Survey
English

B.Mallikarjuna Reddy, P Chandrasekhar, M.Ramakrishna Reddy
2015 International Journal of Computer Trends and Technology  
Technology with its usability varies with time and constraint, for which these day's we call technology of Software as changing technology.  ...  In mixed data extract the useful biological sequences data with subgroup discovery iterative genetic algorithm, Cluster based fuzzy genetic algorithm mining framework, hierarchical fuzzy rule based systems  ...  Technology with its usability varies with time and constraint, for which these day's we call technology of Software as changing technology.  ... 
doi:10.14445/22312803/ijctt-v22p110 fatcat:ag36qn6m4jdkhlakxvrbbisyma

GPR: A Data Mining Tool Using Genetic Programming

Balasubramaniam Ramesh
2001 Communications of the Association for Information Systems  
In this paper, we present a novel approach to data mining that uses the principles of genetic programming to generate production rules from databases.  ...  Using a personnel database of 12,787 employees with 35 descriptive variables, our technique is able to discover employees' hidden decision making patterns in the form of production rules.  ...  The ability of discovering knowledge from databases using GP is illustrated in the LOGENPRO system [Wong et al., 2000] . This system learns logic programs from noisy databases.  ... 
doi:10.17705/1cais.00506 fatcat:xbklzxyinjgtfj7ifchudm4j74

Survey on Big Data Mining Algorithms

Anushree Raj
2019 International Journal for Research in Applied Science and Engineering Technology  
It has been a distinct knowledge that massive amount of data have been generated continuously at extraordinary and ever increasing scales.  ...  Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences.  ...  Data mining is the process of discovering interesting patterns and knowledge from large amounts of data [5] .  ... 
doi:10.22214/ijraset.2019.6234 fatcat:dgcttowerjdkxhu334janvz5z4

Optimization of Association Rule Mining using FP_Growth Algorithm with GA

Abhishek Kumar Singh
2017 International Journal for Research in Applied Science and Engineering Technology  
The objective of this paper is to compare the performance of the genetic algorithm for association rule mining by combining it with other algorithms.  ...  Apriori+fpga and firefly+fpga with traditional apriori and ga.  ...  INTRODUCTION Data mining is a promising and relatively new technology and it is defined as a process of discovering hidden, valuable information by analyzing large amount of data storing in databases or  ... 
doi:10.22214/ijraset.2017.4155 fatcat:khh3o7gjnfebtggqrqalbrocea

Guest editorial data mining and knowledge discovery with evolutionary algorithms

A. Ghosh, A.A. Freitas
2003 IEEE Transactions on Evolutionary Computation  
At present his main research interests are data mining, bioinspired algorithms, and bioinformatics.  ...  He has organized two international workshops on data mining with evolutionary algorithms and delivered tutorials on this theme in several international conferences.  ...  D ATA mining (DM) consists of extracting interesting knowledge from real-world, large and complex data sets; and is the core step of a broader process, called knowledge discovery from databases (KDD)  ... 
doi:10.1109/tevc.2003.819653 fatcat:54tztyosefb2zef24uuuj3lvme

Review on Various Rare Association Rule Mining Algorithms in Big Data

Anjana. K
2018 International Journal for Research in Applied Science and Engineering Technology  
The aim is to propose a new Genetic Algorithm to get rare and interesting association rules on Big Data.  ...  The algorithm must be designed to enable parallel computing and work efficiently over emerging technologies such as Spark and Flink.  ...  An optimized algorithm which can handle Big data combined with the interestingness constraint can generate interesting and rare association rules which can prove to be very useful in applications like  ... 
doi:10.22214/ijraset.2018.4518 fatcat:a4ttw4izqze2blyhzejnp3yejm

Mining Of Interesting Prediction Rules With Uniform Two-Level Genetic Algorithm

Bilal Alatas, Ahmet Arslan
2007 Zenodo  
The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces.  ...  In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem  ...  INTRODUCTION ATA mining (DM) consists of the discovery of highly accurate, comprehensible and interesting (novel) knowledge from large databases.  ... 
doi:10.5281/zenodo.1070346 fatcat:krjaio4vjbfmzobc5cegbbadtq

Analytical Study of Association Rule Mining Methods in Data Mining

Bhavesh M. Patel, Vishal H. Bhemwala, Dr. Ashok R. Patel
2018 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
As we have a tendency to operate with immense historical information (homogeneous or heterogeneous), it is important to spot frequent patterns quickly and accurately.  ...  There are such a large amount of algorithms that provides simple and effective method of association rule mining, however still some analysis is required which might improve potency of association rule  ...  Dehuri S. et al. [16] bestowed a quick and climbable multi-objective association rule mining technique with the use of genetic algorithmic rule from massive database.  ... 
doi:10.32628/cseit1833244 fatcat:ndopsdk6enfr7hphvuhmiym43e

Genetic Programming Approach To Hierarchical Production Rule Discovery

Basheer M. Al-Maqaleh, Kamal K. Bharadwaj
2007 Zenodo  
This paper focuses on the issue of mining generalized rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery.  ...  Finally, Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy. Experimental results are presented to demonstrate the performance of the proposed algorithm.  ...  GENETIC PROGRAMMING APPROACH As a post-processing scheme, we are using GP to discover crisp hierarchical production rules from the flat rules as input.  ... 
doi:10.5281/zenodo.1074458 fatcat:hhuatdkmorditpcmqqwrj6253q

IEEE Access Special Section Editorial: Utility-Pattern Mining: Theoretical Analytics and Applications

Jerry Chun-Wei Lin, Philippe Fournier-Viger, Vincent S. Tseng, Philip S. Yu
2021 IEEE Access  
The proposed algorithm is based on the grouping genetic algorithm (GGA), with chromosome representation and fitness function designed for the purpose of finding a suitable DGSP.  ...  Utility-pattern mining in data has received a lot of attention from the knowledge discovery in database (KDD) community due to its high potential for many applications such as finance, biomedicine, manufacturing  ... 
doi:10.1109/access.2021.3051446 fatcat:vgbgbx4wjrfnthknj23e36lyim

A Genetic Algorithm for Discovering Classification Rules in Data Mining

Basheer M.Al-Maqaleh, Hamid Shahbazkia
2012 International Journal of Computer Applications  
In this paper, a genetic algorithm-based approach for mining classification rules from large database is presented.  ...  Data mining has as goal to discover knowledge from huge volume of data.  ...  useful information and interesting knowledge from a massive amount of data, providing valuable support for decision making in industry, business, government, and science [1] , [2] .  ... 
doi:10.5120/5644-8072 fatcat:7mwbmybgjbfpdlaflwxag53rca

Application of Data Mining in Knowledge Management: A Review

2021 International Journal of Advanced Trends in Computer Science and Engineering  
The discussion on the result is divided into four topics: (1) knowledge resource, (2) knowledge datasets, (3) data mining tasks, and (4) data mining algorithms.  ...  This paper first briefly describes the concept of data mining and knowledge management.  ...  It is apparent that Web Systems and Technology can have a beneficial effect on the practice of data mining and knowledge management, and that should be an interesting area for future information systems  ... 
doi:10.30534/ijatcse/2021/061042021 fatcat:ojj5o3mmjfgcdbz72wzdse5uky

Mining Sequential Patterns Using Hybrid Evolutionary Algorithm

Mourad Ykhlef, Hebah ElGibreen
2009 Zenodo  
Nowadays, some evolutionary algorithms, such as Particle Swarm Optimization and Genetic Algorithm, were proposed and have been applied to solve this problem.  ...  This paper will introduce a new kind of hybrid evolutionary algorithm that combines Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) to mine Sequential Pattern, in order to improve the speed  ...  ACKNOWLEDGMENT The authors acknowledge the cooperation of King Faisal Specialist Hospital and Research Centre, in KSA, for providing a real pharmacy database for this work experiment.  ... 
doi:10.5281/zenodo.1330237 fatcat:vjcfwga4pzbh7fn23ia7757o6e

Optimizing Spatial Trend Detection By Artificial Immune Systems

M. Derakhshanfar, B. Minaei-Bidgoli
2009 Zenodo  
Spatial trends are one of the valuable patterns in geo databases. They play an important role in data analysis and knowledge discovery from spatial data.  ...  In an evolutionary process with artificial immune algorithm, affinity of low trends is increased with mutation until stop condition is satisfied.  ...  These are valuable mines of knowledge vital for strategic decision making and motivate the highly demanding field of spatial data mining i.e., discovery of interesting, implicit knowledge from large amount  ... 
doi:10.5281/zenodo.1328650 fatcat:mbxbuzj735dhdn2ub7gndkxu3y
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