Search Results - (( java implementation modified algorithm ) OR ( knowledge solving mining algorithm ))
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1
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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2
Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms
Published 2018“…Bankruptcy classification and prediction are imperative for informed decision making and problem-solving in actual risk assessment. Knowledge discovery using data mining techniques are commonly applied in bankruptcy classification and prediction. …”
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3
A novel approach to data mining using simplified swarm optimization
Published 2011“…Therefore, the proposed SSO rule-based classifier with local search strategies has offered a new paradigm shift in solving complex problems in data mining which may not be able to be solved by other benchmark classifiers.…”
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4
Intelligent mining of large-scale bio-data: bioinformatics applications
Published 2017“…Bioinformatics creates heuristic approaches and complex algorithms using artificial intelligence and information technology in order to solve biological problems. …”
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5
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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6
Data Classification and Its Application in Credit Card Approval
Published 2004“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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7
Automatic clustering of gene ontology by genetic algorithm
Published 2006“…Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. Therefore, an approach for solving the automatic clustering of the Gene Ontology is proposed by incorporating cohesion-and-coupling metric into a hybrid algorithm consisting of a genetic algorithm and a split-and-merge algorithm. …”
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8
Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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9
Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks
Published 2019“…We develop an efficient iterative algorithm to optimize it since the objective function of the proposed method is non-smooth and difficult to solve. …”
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10
Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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11
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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12
Improving intrusion detection using genetic algorithm
Published 2013“…GA functions on a number of possible solutions using the principle of survival of the fittest with the aim to generate better approximations to solve a particular problem GA is facing. The validity of this approach is verified using Knowledge Discovery and Data Mining Cup 1999 (KDD Cup ’99) dataset. …”
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13
Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…Therefore, it can be solved by using population-based techniques such as Genetic Algorithm and Particle Swarm Optimization. …”
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14
Multi agent and artificial neural networks prediction framework development for stock investment strategy
Published 2016“…WMA comprises of an algorithm for web mining which enables it to mine and extract semi-structured information and create new structured information using ontology. …”
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15
Multi-agent and artificial neural networks prediction framework development for stock investment strategy
Published 2016“…WMA comprises of an algorithm for web mining which enables it to mine and extract semi-structured information and create new structured information using ontology. …”
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16
Ranking-based pruning and weighted support model for gene association in frequent itemsets / Sofianita Mutalib
Published 2019“…Biological domain is one of the critical areas that always seek for useful knowledge and patterns observed through available methods, including data mining. …”
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17
Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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18
Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…The goal of data mining is to find rules that model the world sufficiently well. …”
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19
Challenges of hidden data in the unused area two within executable files
Published 2009“…Results: The programs were coded in Java computer language and implemented on Pentium PC. …”
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20
Problem restructuring in interger programming for reduct searching
Published 2003“…In effect, they are very useful in generating rules when solving the classification problem that is inherent in data mining. …”
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