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On the Suitability of Genetic-Based Algorithms for Data Mining [chapter]

Sunil Choenni
1999 Lecture Notes in Computer Science  
We focus on the suitability of genetic-based algorithms for data mining. We discuss the design and implementation of a genetic-based algorithm for data mining and illustrate its potentials.  ...  Therefore, efficient search strategies are of vital importance. Search strategies on genetic-based algorithms have been applied successfully in a wide range of applications.  ...  Hein Veenhof and Egbert Boers from NLR are thanked for their valuable comments on earlier drafts of this paper.  ... 
doi:10.1007/978-3-540-49121-7_5 fatcat:qal3fslqmrdxbltsuqukpqfke4

A Survey of Bio Inspired Algorithms for Web Information Extraction and Optimization for Big Data Analytics

2020 International Journal of Engineering and Advanced Technology  
Some of the tools that are available for data extraction and mining are DataMelt, Apache Mahout, Weka, Orange and Rapid Miner for enhancing web data extraction efficiency.  ...  Genetic algorithms are purely heuristic in nature and are employed for computation and extracting information and from big data.  ...  Bat Algorithm This algorithm is based on behavior of bats in the eco system to search its food, which emits pulse rate and loudness based on availability of its prey.  ... 
doi:10.35940/ijeat.b2011.1210220 fatcat:4fnpnyunnjdrvci7qyubmpxjwm

An effective parallel approach for genetic-fuzzy data mining

Tzung-Pei Hong, Yeong-Chyi Lee, Min-Thai Wu
2014 Expert systems with applications  
The time complexities for both sequential and parallel genetic-fuzzy mining algorithms have also been analyzed, with results showing the good effect of the proposed one.  ...  Applying the master-slave parallel architecture to speed up the genetic-fuzzy data mining algorithm is thus a feasible way to overcome the low-speed fitness evaluation problem of the original algorithm  ...  As to parallel data mining, Agrawal and Shafer proposed three parallel mining algorithms based on the Apriori algorithm for speeding up the mining process (Agrawal & Shafer, 1996) .  ... 
doi:10.1016/j.eswa.2013.07.090 fatcat:5a4bjgrsijbhxb5b4lo2jc37fq


RK Dhuware, SR Pande, SJ Sharma
2018 International Journal of Advanced Research  
Overview of Knowledge Discovery and Data Mining:-KDD focuses on the overall process of knowledge discovery from large volumes of data, including the storage and accessing of such data, scaling of algorithms  ...  to massive data sets, interpretation and visualization of results, and the modeling and support of the overall human machine interaction.  ...  on the suitability of an approach.  ... 
doi:10.21474/ijar01/6834 fatcat:ez3i6rcihrgbjnkbpe7he6dbwq

An improved approach to find membership functions and multiple minimum supports in fuzzy data mining

Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng
2009 Expert systems with applications  
In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting minimum supports and membership functions for items from quantitative transactions.  ...  The approach is called divide-and-conquer genetic-fuzzy mining algorithm for items with Multiple Minimum Supports (DGFMMS), and is designed for finding minimum supports, membership functions, and fuzzy  ...  A GA-based framework with the divide-and-conquer strategy is proposed for searching for minimum supports and sets of membership functions suitable for the mining problems.  ... 
doi:10.1016/j.eswa.2009.01.067 fatcat:iu2ywpoizjhvhghtzxgy34duny

A Comparative Study on Temporal Mobile Access Pattern Mining Methods

Hanan Fahmy, Maha A.Hana, Yahia K.
2012 International Journal of Advanced Computer Science and Applications  
Existing mining methods have proposed frequent mobile user's behavior patterns statistically based on requested services and location information.  ...  Recently the algorithms of discovering frequent mobile user's behavior patterns have been studied extensively.  ...  Work mechanisms for Temporal Mobile Access Pattern [18] TMSP refer to TMAP-mine algorithm [8] without using time interval but using genetic algorithm to discover the most suitable time intervals by  ... 
doi:10.14569/ijacsa.2012.030323 fatcat:orfdb7mc3fbovneuz36why5kaa

Data mining techniques for herbs

J Satish Babu, M Niveditha, V Bhavya, K Gowthami
2017 International Journal of Engineering & Technology  
The main objective of this project is to survey on various data mining methods and their techniques and to conclude the suitable algorithm.  ...  Moreover Nagoya protocol is most commonly used in selection of herbs based on similar efficiency, Later scientists have voiced their concern on protocol also proved it as less effective therefore, this  ...  By using some commonly used Data Mining tasks we can achieve the required result of prediction and description. 1) Classification is used to classify data based on attribute type also based on the category  ... 
doi:10.14419/ijet.v7i1.1.9943 fatcat:342syjq7afa4tclqzt6grugioy

Genetic-Fuzzy Data Mining With Divide-and-Conquer Strategy

Tzung-Pei Hong, Chun-Hao Chen, Yeong-Chyi Lee, Yu-Lung Wu
2008 IEEE Transactions on Evolutionary Computation  
A genetic algorithm (GA)-based framework for finding membership functions suitable for mining problems is proposed.  ...  This paper, thus, proposes a fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions.  ...  These relationships are not based on inherent properties of the data themselves (as with functional dependencies), but rather based on co-occurrence of the data items.  ... 
doi:10.1109/tevc.2007.900992 fatcat:apl7s2ebgzfcrddxa6slaadaay

Role and Applications of Genetic Algorithm in Data Mining

Gunjan Verma, Vineeta Verma
2012 International Journal of Computer Applications  
In this paper, we discuss the suitability of genetic-based algorithms for data mining.  ...  Search strategies based on genetic-based algorithms have been applied successfully in a wide range of applications.  ...  USE OF GENETIC ALGORITHM IN DATA MINING In this paper, we discuss the applicability of a genetic-based algorithm to the search process in data mining.  ... 
doi:10.5120/7438-0267 fatcat:55b5rbys7fe5ldd3tunv4a2hsm

Process Mining a Comparative Study
IJARCCE - Computer and Communication Engineering

2014 IJARCCE  
Its primary objective is the discovery of process models based on available event log data.  ...  This paper proposes a solution to evaluate and compare these process mining algorithms efficiently, so that businesses can efficiently select the process mining algorithms that are most suitable for a  ...  WHY PROCESS MINING The emergence of semi-structured processes, combined with improvements in computing power and the speed of data transmission, have fueled the need for mining algorithms to address new  ... 
doi:10.17148/ijarcce.2014.31154 fatcat:wo7ah4vr45ghhaf67xvpue23oy

A Novel Optimal Pattern Mining Algorithm using Genetic Algorithm

Vishakha Agarwal, Akhilesh Tiwari
2016 International Journal of Computer Applications  
Pattern Mining is one such technique to mine useful patterns out of the pattern warehouse. Patterns are the one way of knowledge representations.  ...  The algorithm uses the features and operators of the genetic algorithm to incorporate the property of optimality among patterns.  ...  CONCLUSION A great deal of work has been done over genetic based frequent pattern mining and genetic based association rule mining.  ... 
doi:10.5120/ijca2016910259 fatcat:nbucpsfhs5gpxd7zj26uk4342m

A GA-based Fuzzy Mining Approach to Achieve a Trade-off Between Number of Rules and Suitability of Membership Functions

Tzung-Pei Hong, Chun-Hao Chen, Yu-Lung Wu, Yeong-Chyi Lee
2006 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
We present a GA-based framework for finding membership functions suitable for mining problems and then use the final best set of membership functions to mine fuzzy association rules.  ...  The fitness of each chromosome is evaluated by the number of large 1-itemsets generated from part of the previously proposed fuzzy mining algorithm and by the suitability of the membership functions.  ...  This research was supported by the National Science Council of the Republic of China under contract NSC93-2213-E-390-001.  ... 
doi:10.1007/s00500-006-0046-x fatcat:uagegx4u7nhyxj5vwrz4tnb73i

Gene Algorithm of Crowd System of Data Mining

Jong-Min Park
2012 Journal of information and communication convergence engineering  
Since grouping in data mining deals with a large mass of data, it lessens the amount of time spent with the source data, and grouping techniques that shrink the quantity of the data form to which the algorithm  ...  In this paper we propose a gene algorithm that automatically decides on the number of grouping algorithms.  ...  It will also help fulfill the purpose of setting a suitable value as a guidepost in finding the right algorithm for data mining.  ... 
doi:10.6109/jicce.2012.10.1.040 fatcat:f2i3h36gjvfxhixdjni6yctqe4

A Literature Review of Personalized Learning Algorithm

Yin Tang, Wen Wang
2018 Open Journal of Social Sciences  
The review aims at elaborating the research based on recommendation system and data mining in personalized learning algorithm and look forward to the future research trend.  ...  The study of personalized learning algorithms meets the need to provide students with the most suitable resources for learning.  ...  However, for the recommendation system based on data mining algorithm, its efficiency depends on which data mining algorithm is adopted.  ... 
doi:10.4236/jss.2018.61009 fatcat:2ivoike2xbbglnkbovgsw6bu2y

Multi-objective rule mining using genetic algorithms

Ashish Ghosh, Bhabesh Nath
2004 Information Sciences  
Based on experimentation, the algorithm has been found suitable for large databases.  ...  Using these three measures as the objectives of rule mining problem, this article uses a Pareto based genetic algorithm to extract some useful and interesting rules from any market-basket type database  ...  Based on this idea, several genetic algorithms were designed to solve multiobjective problems [13, 25, 26] . Multiple-Objective Genetic Algorithm (MOGA) [13] is one of them.  ... 
doi:10.1016/j.ins.2003.03.021 fatcat:n6f7jjbqhvervghtzdpepyn6o4
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