Search Results - (( pattern mining algorithm ) OR ((( pattern bees algorithm ) OR ( pattern search algorithms ))))*

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  1. 1
    Frequent Lexicographic Algorithm for Mining Association Rules

    Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

    Published 2005
    “…An algorithm called Flex (Frequent lexicographic patterns) has been proposed in obtaining a good performance of searching li-equent patterns. …”
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  2. 2
    An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP

    An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP by Saputra, Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of applications. …”
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  3. 3
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, N., Sulaiman, M.N., Othman, M., Selamat, M.H.

    Published 2002
    “…Frequent pattern mining is a key problem in important data mining applications, such as the discovery of association rules, strong rules and episodes. …”
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  4. 4
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, Norwati, Sulaiman, Md. Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2002
    “…Frequent pattern mining is a key problem in important data mining applications, such as the discovery of association rules, strong rules and episodes. …”
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  5. 5
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Even the smart people are unable to report an email as a spam when the spammer tries to defraud them. The aim of data mining is to search and find undetermined patterns in huge databases. …”
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  6. 6
    Frequent itemset mining in high dimensional data: a review

    Frequent itemset mining in high dimensional data: a review by Md. Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza

    Published 2019
    “…Finally, the paper reviews on the latest algorithms of colossal frequent itemset/pattern which currently is the most relevant to mining highdimensional dataset.…”
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  7. 7
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The proposed method, XiFLEX has been implemented using two different techniques (java based & XQuery) and compared with the original FLEX algorithm in its basic implementation and the Apriori algorithm for frequent patterns generation. …”
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  8. 8
    Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data

    Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data by Laxmi Lydia E., Sharmili N., Nguyen P.T., Hashim W., Maseleno A.

    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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  9. 9
    Data normalization techniques in swarm-based forecasting models for energy commodity spot price

    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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  10. 10
    Using Pattern Search Methods for Minimizing Clustering Problems

    Using Pattern Search Methods for Minimizing Clustering Problems by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June, Mohagheghtabar, Maryam

    Published 2010
    “…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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  11. 11
    Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System

    Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

    Published 2013
    “…The fruit flies or Drosophila Melanogaster movement strategy offers some advantages such as strategic 'search-aggregation' cycle, distribution of moving patterns with Levy Random, information sharing in real-time, and reduction of controller parameters during movements. …”
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  12. 12
    Using language-based search in mining large software repositories

    Using language-based search in mining large software repositories by Awang Abu Bakar, Normi Sham

    Published 2011
    “…For the purpose of automating the data retrieval from the repository, a parser was written using the Python programming language, and based on the pattern matching algorithm. The retrieved data were later used to estimate the quality of the open source software.…”
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  13. 13
    Artificial neural networks based optimization techniques: A review

    Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

    Published 2023
    “…In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”
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  14. 14
    Using language-based search in mining large software repositories

    Using language-based search in mining large software repositories by Awang Abu Bakar, Normi Sham

    Published 2011
    “…For the purpose of automating the data retrieval from the repository, a parser was written using the Python programming language, and based on the pattern matching algorithm. The retrieved data were later used to estimate the quality of the open source software.…”
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  15. 15
    ZigBee environment for indoor localization

    ZigBee environment for indoor localization by Chieh K.S., Keong N.Y., Burhan M.F., Balasubramaniam N., Din N.M.

    Published 2023
    “…Nearest neighbor search; Pattern recognition; Zigbee; Indoor environment; Indoor localization; Indoor localization systems; Indoor locations; K nearest neighbor algorithm; Prediction accuracy; Indoor positioning systems…”
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  16. 16
    An analysis of text mining factors enhancing the identification of relevant studies

    An analysis of text mining factors enhancing the identification of relevant studies by Khashfeh M., Mahmoud M.A., Ahmad M.S.

    Published 2023
    “…In addition, it provides an input tool for user�s search preferences. The second component is the search process that is operated by a pattern matching. …”
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  17. 17
    Data mining techniques for disease risk prediction model: A systematic literature review

    Data mining techniques for disease risk prediction model: A systematic literature review by Ahmad W.M.T.W., Ghani N.L.A., Drus S.M.

    Published 2023
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  18. 18
    An improved ACS algorithm for data clustering

    An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…Data clustering is a data mining technique that discovers hidden patterns by creating groups (clusters) of objects. …”
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  19. 19
    Lexicon-based and immune system based learning methods in Twitter sentiment analysis

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    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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  20. 20
    Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms

    Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms by Mohammadi, M., Musa, S.N., Bahreininejad, A.

    Published 2015
    “…The aim is to determine the optimal production rate, production frequency, cycle time, as well as a feasible manufacturing schedule for the family of items, and to minimize the long-run average costs. Efficient search procedures are presented to obtain the optimum solutions by employing four well-known metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), and artificial bee colony (ABC). …”
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