Search Results - (( pattern mining algorithm ) OR ((( patterns growth algorithm ) OR ( patterns ant algorithm ))))
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DFP-growth: An efficient algorithm for mining frequent patterns in dynamic database
Published 2012“…Therefore, in this paper we introduce an efficient algorithm called Dynamic Frequent Pattern Growth (DFP-Growth) to mine the frequent patterns from dynamic database. …”
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2
A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. …”
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3
A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows.First, it compresses the database representing frequent items into a frequent-pattern tree, or FP-tree, which retains the itemset association information. …”
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4
Using unique-prime-factorization theorem to mine frequent patterns without generating tree
Published 2011“…An interest solution is to design an approach that without generating candidate is able to mine frequent patterns. Results: An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. …”
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5
ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
Published 2017“…Therefore, in this paper we proposed a complete model for mining least patterns known as Efficient Least Pattern Mining Model (ELP-M2) with LP-Tree data structure and LP-Growth algorithm. …”
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6
Discovering Pattern in Medical Audiology Data with FP-Growth Algorithm
Published 2012“…We use frequent pattern growth (FP-Growth) algorithm in the data processing step to build the FP-tree data structure and mine it for frequents itemsets. …”
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7
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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The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment
Published 2007“…This , paper discusses the development of data mining and pattern recognition algorithm to handle the complexity of hyperspectral remote sensing images in Geographical Information Systems environment. …”
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10
An improved ACS algorithm for data clustering
Published 2020“…Data clustering is a data mining technique that discovers hidden patterns by creating groups (clusters) of objects. …”
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EFP-M2: Efficient model for mining frequent patterns in transactional database
Published 2012“…Therefore, we propose an Efficient Frequent Pattern Mining Model (EFP-M2) to mine the frequent patterns in timely manner. …”
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Mining dense data: Association rule discovery on benchmark case study
Published 2016“…In this article, we present comparison result between Apriori and FP-Growth algorithm in generating association rules based on a benchmark data from frequent itemset mining data repository. …”
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A partition based feature selection approach for mixed data clustering / Ashish Dutt
Published 2020“…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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14
Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Most of the previous works explore Apriori approach which is not efficient in mining plentiful and long patterns. In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. …”
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15
A Scalable Algorithm for Constructing Frequent Pattern Tree
Published 2014“…The construction of FP-Tree is very important prior to frequent patterns mining. However, there have been too limited efforts specifically focused on constructing FP-Tree data structure beyond from its original database. …”
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Modeling the impacts of constant price GDP and population on CO2 emissions using Cobb-Douglas model and ant colony optimization algorithm
Published 2019“…Modeling is done by using Cobb-Douglas model production function, where parameter estimation is done by using ant colony optimization algorithm. Furthermore, model estimators are used for forecasting CO emission concentrations. …”
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17
Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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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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Mining Sequential Patterns using I-PrefixSpan
Published 2008“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. …”
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Citation Index Journal -
20
Development of a Web Access Control Technique Based User Access Behavior
Published 2004“…A set of algorithms is used for mining user access behavior, preprocessing tasks for data preparation, association rules for defining the rules that describe the correlation between web user access transaction entries patterns, and sequential pattern discovery for finding the sequences of the web user access transaction entries pattern using Prefixspan (Pattern growth via frequent sequence lattice) algorithms. …”
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