Search Results - (( pattern extraction mining algorithm ) OR ( parallel distribution process algorithm ))
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…Four datasets from UCI machine learning repositories and domain theories except the pumsb dataset were experimented. The Flex algorithm and the other two existing algorithms Apriori and DIC under the same specification are tested toward these datasets and their extraction times for mining frequent patterns were recorded and compared. …”
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Mining least relational patterns from multi relational tables
Published 2005“…In this paper, we propose an algorithm called Extraction Least Pattern (ELP) algorithm that using a couple of predefined minimum support thresholds. …”
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Improving mining efficiency: A new scheme for extracting association rules
Published 2009“…In the age of information technology, the amount of accumulated data is tremendous. Extracting the association rule from this data is one of the important tasks in data mining.Most of the existing association rules in algorithms typically assume that the data set can fit in the memory.In this paper, we propose a practical and effective scheme to mine association rules from frequent patterns, called Prefixfoldtree scheme (PFT scheme).The original dataset is divided into folds, and then from each fold the frequent patterns are mined by using the tree projection approach.These frequent patterns are combined into one set and finally interestingness constraints are used to extract the association rules.The experiments will be conducted to illustrate the efficiency of our scheme.…”
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Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin
Published 2006“…Data mining is primarily used in finance and business environment to extract knowledge from financial, retail, communication and marketing data. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Social media mining is the process of collecting large datasets from user-generated content and extracting and analyzing social media interactions to recognize meaningful patterns in individual and social behavior. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Social media mining is the process of collecting large datasets from user-generated content and extracting and analyzing social media interactions to recognize meaningful patterns in individual and social behavior. …”
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Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.]
Published 2024“…The proposed method is based on comparing two algorithms: Apriori and Frequent Pattern Growth (FP- Growth). …”
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Direct approach for mining association rules from structured XML data
Published 2012“…Having the ability to extract information from XML data would answer the problem of mining the web contents which is a very useful and required power nowadays. …”
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10
Mining Web usage using FRS
Published 2018“…Web Usage Mining (WUM) is the application of data mining methods in extracting potentially useful information from web usage data. …”
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Proceeding Paper -
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Discovering association rules for mining images datasets: a proposal
Published 2005“…The algorithm has four major steps: feature extraction, object identification, auxiliary image creation and object mining. …”
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A new classification model for online predicting users' future movements
Published 2008“…The WUM can model user behavior and, therefore, to forecast their future movements by mining user navigation patterns. To provide online prediction efficiently, we advance architecture for online predicting in web usage mining system by proposing novel model based on Longest Common Subsequence algorithm for classifying user navigation patterns. …”
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Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023Subjects:Article -
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Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
Published 2012“…This project focuses on step-up cluster computing and a parallel Genetic Algorithm. The objectives of this project to set-up Beowulf cluster computer to apply the Travelling Salesman Problem in parallel by using Genetic Algorithms and evaluate sequential algorithms and parallel algorithms by Genetic Algorithms. …”
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16
Communication and computational cost on parallel algorithm of PDE elliptic type
Published 2009“…The parallel algorithms of 2-dimensional Partial Differential Equation (PDE) elliptic type for the prediction will be executed using distributed memory of heterogeneous cluster platform on LINUX-based environment. …”
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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…Geographically distributed heterogeneous resources can execute such workflows in parallel. …”
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Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data
Published 2023“…Automatic indexing; Big data; Cluster analysis; Extraction; Factorization; Indexing (of information); Information retrieval; K-means clustering; Natural language processing systems; Open source software; Open systems; Pattern matching; Software quality; Software testing; Text mining; Hadoop; Key phrase extractions; Map-reduce; Pattern-matching technique; Porters; Pre-processing algorithms; Software environments; Unlabeled; Matrix algebra…”
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A web usage mining approach based on LCS algorithm in online predicting recommendation systems
Published 2008“…To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS algorithm for classifying user navigation patterns for predicting users' future requests. …”
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Feature selection with integrated Gaussian seahorse optimization data mining for cross-border business cooperation between the Malaysian medical industry and tourism industry
Published 2023“…The integrated GSH-DM model then applies the Gaussian Seahorse Optimization algorithm to optimize the data mining process, enhancing the accuracy and efficiency of pattern discovery. the GSH-DM model, this study aims to uncover hidden patterns, relationships, and predictive models that can guide decision-making and strategy development for cross-border business cooperation. …”
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