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  1. 1
    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
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  2. 2
    Web-based expert system for material selection of natural fiber- reinforced polymer composites

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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  3. 3
    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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  4. 4
    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption

    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

    Published 2019
    “…In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. …”
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  5. 5
    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
    “…There are several techniques to mine association rules from XML data. The basic approach is to map the XML documents to relational data model and to store them in a relational database. …”
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  6. 6
    A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption

    A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption by Haruna, Chiroma, Abdullahi, Usman Ali, Targio Hashem, Ibrahim Abaker, Saadi, Younes, Al-Dabbagh, Rawaa Dawoud, Ahmad, Muhammad Murtala, Emmanuel Dada, Gbenga, Danjuma, Sani, Maitama, Jaafar Zubairu, Abubakar, Adamu, Abdulhamid, Shafi’i Muhammad

    Published 2019
    “…In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. …”
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  7. 7
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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  8. 8
    Constraint preserving mapping algorithm for XML storage

    Constraint preserving mapping algorithm for XML storage by Ahmad, Kamsuriah, Mamat, Ali, Ibrahim, Hamidah, Mohd Noah, Shahrul Azman

    Published 2006
    “…Especially the structure of an XML document is hierarchy and the XML elements may be nested and repeated. So it is also useful in information exchange and data integration for preserving the semantics of data originating in XML to relational databases. …”
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  9. 9
    An ensemble data summarization approach based on feature transformation to learning relational data

    An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

    Published 2015
    “…In the process of summarizing data, the data stored in multi-relational database need to be transformed into Term Frequency - Inverse Document Frequency (TF-IDF) vector space. …”
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  10. 10
    Clustering algorithm for market-basket analysis : the underlying concept of data mining technology

    Clustering algorithm for market-basket analysis : the underlying concept of data mining technology by Abdul Kadir, Khairil Annuar

    Published 2003
    “…In this research, the author tried to relate the algorithm presented with the experiment. …”
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  11. 11
    Optimized feature construction methods for data summarizations of relational data

    Optimized feature construction methods for data summarizations of relational data by Sze, Florence Sia Fui

    Published 2014
    “…Many approaches have been developed to discover knowledge (i.e. useful information) from data stored in multiple tables in a relational database. …”
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  12. 12
    Dimensionality reduction in data summarization approach to learning relational data

    Dimensionality reduction in data summarization approach to learning relational data by Kheau, Chung Seng, Rayner Alfred, Lau, Hui Keng

    Published 2013
    “…The DARA algorithm is designed to summarize data and it is one of the approaches introduced in relational data mining in order to handle data with one-to-many relations. …”
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  13. 13
    Normalized Relational Storage for Extensible Markup Language (XML) Schema

    Normalized Relational Storage for Extensible Markup Language (XML) Schema by Kamsuriah, Ahmad, Reduan, Samad

    Published 2011
    “…Approach: In this study we present an algorithm for generating an optimal design for XML in relational setting. …”
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  14. 14
    XRecursive, An Efficient Relational Method to Store XML Data

    XRecursive, An Efficient Relational Method to Store XML Data by Jasni, Mohamad Zain, K.F., Rabbi, M.A., Ibrahim Fakharaldien, Norrozila, Sulaiman

    Published 2011
    “…The steps and algorithm are given in details to describe how to use the storing structure to storage and query XML documents in relational database. …”
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  15. 15
    Clustering Student Performance Data Using k-Means Algorithms

    Clustering Student Performance Data Using k-Means Algorithms by Sultan Alalawi, Sultan Juma, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

    Published 2023
    “…Education institutions store large amounts of data regarding students, such as demographics, academic-related data, and student activities. …”
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  16. 16
    A new algorithm to measure relevance among Web pages

    A new algorithm to measure relevance among Web pages by Sadi, M.S., Rahman, M.M. Hafizur, Horiguchi, Susumu

    Published 2006
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  17. 17
    Data discovery algorithm for scientific data grid environment

    Data discovery algorithm for scientific data grid environment by Abdullah, Azizol, Othman, Mohamed, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Othman, Abu Talib

    Published 2005
    “…By using this model, we study various discovery algorithms for locating data sets in a data grid system. …”
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  18. 18
    Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob

    Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob by Yaacob, Siti Hajar

    Published 2014
    “…The objectives of this research are data mining are used to extract useful data from sales and product. …”
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  19. 19
    Analysis of Chinese patents associated with incremental clustering algorithms: A review / Archana Chaudhari

    Analysis of Chinese patents associated with incremental clustering algorithms: A review / Archana Chaudhari by Chaudhari, Archana, Mulay, Preeti, Kumar Tiwari, Amit

    Published 2022
    “…This learning is incremental in nature for all involved entities and users, as the data is growing exponentially in real-time. To achieve learning from such dynamic data sources, incremental clustering algorithms are used mandatorily. …”
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  20. 20
    An improved self organizing map using jaccard new measure for textual bugs data clustering

    An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

    Published 2018
    “…Considering the unsupervised learning algorithms, Self-Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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