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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
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    Thesis
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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  6. 6
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  7. 7
    Improved normalization and standardization techniques for higher purity in K-means clustering

    Improved normalization and standardization techniques for higher purity in K-means clustering by Dalatu, Paul Inuwa, Fitrianto, Anwar, Mustapha, Aida

    Published 2016
    “…Clustering is an unsupervised classification method with aim of partitioning, where objects in the same cluster are similar, and objects belong to different clusters vary significantly, with respect to their attributes. The K-means algorithm is a famous and fast technique in non-hierarchical cluster algorithms. …”
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  8. 8
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  9. 9
    JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation

    JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation by Abu, Ahmad Zaidee

    Published 2008
    “…It is also shown that this technique is fully format compliance as most of other techniques do. …”
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  10. 10
    An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms

    An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms by Zahid, Aafaq

    Published 2015
    “…It is concluded that the resultant hybrid techniques can perform well if the variables provided to normalization by neighborhood model (MF and CF) do not have big differences in order for the hybrid normalization model to outperform every algorithm in comparison.…”
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  11. 11
    An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma

    An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma by Sani , Danjuma

    Published 2017
    “…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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  12. 12
    Text normalization algorithm for facebook chats in Hausa language

    Text normalization algorithm for facebook chats in Hausa language by Jaafar, Zubairu Maitama, Haruna, Usman, Gambo, Abdullahi Ya'u, Thomas, Bimba Andrew, Idris, Norisma, Ya’u Gital, Abdulsalam, Abubakar, Adamu

    Published 2014
    “…It was found that our proposed algorithm was able to normalized Hausa NSWs with an accuracy of 100%. …”
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    Proceeding Paper
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  13. 13
    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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  14. 14
    The Impact of Normalization Techniques on Performance Backpropagation Networks

    The Impact of Normalization Techniques on Performance Backpropagation Networks by Norlida, Hassan

    Published 2004
    “…This study explored several normalization techniques using backpropagation learning. …”
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  15. 15
    Design and analysis of sequence generator module using eulerian path algorithm for DNA fragment assembly / Mustaqim Mohd Subri

    Design and analysis of sequence generator module using eulerian path algorithm for DNA fragment assembly / Mustaqim Mohd Subri by Mohd Subri, Mustaqim

    Published 2013
    “…This project is to design and analysis the sequence generator module using Eulerian Path algorithm for DNA fragment assembly. Traditionally, “overlap-layoutconsensus” technique is used for DNA fragment assembly, but this technique has a problem in assembling a long sequence of DNA which a new technique needs to be used to overcome this problem. …”
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  16. 16
    A robust technique of brain MRI classification using color features and k-nearest neighbor algorithm

    A robust technique of brain MRI classification using color features and k-nearest neighbor algorithm by Fayaz, Muhammad, Shah, Abdul Salam, Wahid, Fazli, Shah, Asadullah

    Published 2016
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  17. 17
    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
    Conference paper
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  18. 18
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…Another possibility is to apply a bootstrap technique which does not rely on the normality assumption. …”
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  19. 19
    A new method for intermediate power point tracking for PV generator under partially shaded conditions in hybrid system

    A new method for intermediate power point tracking for PV generator under partially shaded conditions in hybrid system by Guichi, Amar, Talha, Abdelaziz, Berkouk, El Madjid, Mekhilef, Saad, Gassab, Samir

    Published 2018
    “…This technique is based on the combination of two algorithms, the particle swarm optimization algorithm for tracking the global maximum power point, while a newly developed algorithm is used for attaining any other supervisory control set point. …”
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  20. 20
    New approaches to normalization techniques to enhance k-means clustering algorithm

    New approaches to normalization techniques to enhance k-means clustering algorithm by Dalatu, Paul Inuwa, Midi, Habshah

    Published 2020
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