Search Results - (( java application using algorithm ) OR ( data extraction patterns algorithm ))

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  1. 1
    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
    “…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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  2. 2
    Pattern Discovery Using K-Means Algorithm

    Pattern Discovery Using K-Means Algorithm by Ahmed, AM, Norwawi, NM, Ishak, WHW, Alkilany, A

    Published 2024
    “…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
    Proceedings Paper
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  3. 3
    Pattern discovery using k-means algorithm

    Pattern discovery using k-means algorithm by Ahmed, Almahdi Mohammed, Wan Ishak, Wan Hussain, Md Norwawi, Norita, Alkilany, Ahmed

    Published 2014
    “…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
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  4. 4
    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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  5. 5
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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    Monograph
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  6. 6
    Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier

    Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier by G. Noma, Nasir, Mohd Khanapi, Abd Ghani, Mohamad Khir , Abdullah, Noorizan , Yahya

    Published 2013
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  7. 7
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
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  8. 8
    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

    Published 2011
    “…Classification and patterns extraction from customer data is very important for business support and decision making. …”
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    Citation Index Journal
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  9. 9
    Improved GART neural network model for pattern classification and rule extraction with application to power systems

    Improved GART neural network model for pattern classification and rule extraction with application to power systems by Yap K.S., Lim C.P., Au M.T.

    Published 2023
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  10. 10
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  11. 11
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…Automated system also saves time and cost as the system is able to process large amount of image data at one time. This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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  12. 12
    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…”
    Article
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  13. 13
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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    Monograph
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  14. 14
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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  15. 15
    Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin

    Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin by Latiffah, A. Noor, Nordin, A. B.

    Published 2006
    “…Data mining can discover patterns or rules from a vast volume of data. …”
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  16. 16
    Social media mining: a genetic based multiobjective clustering approach to topic modelling

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…As the components of big data continue to expand, the task of extracting useful information becomes critical. …”
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  17. 17
    Pattern Recognition for Human Diseases Classification in Spectral Analysis

    Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

    Published 2022
    “…Exploratory data analysis is an approach that involves detecting anomalies in data, extracting essential variables, and revealing the data’s underlying structure. …”
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  18. 18
    Temporal - spatial recognizer for multi-label data

    Temporal - spatial recognizer for multi-label data by Mousa, Aseel

    Published 2018
    “…Hence, there is a need for a recognition algorithm that can separate the overlapping data points in order to recognize the correct pattern. …”
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  19. 19
    Pattern discovery using k-means algorithm

    Pattern discovery using k-means algorithm by Mohammed Ahmed A., Wan Ishak W.H., Md Norwawi N., Alkilany A.

    Published 2024
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  20. 20
    Improving mining efficiency: A new scheme for extracting association rules

    Improving mining efficiency: A new scheme for extracting association rules by Said, Aiman Moyaid, Dominic, P D D., Abdullah, Azween

    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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