Search Results - ((((mining algorithm) OR (_ algorithm))) OR (((matching algorithm) OR (learning algorithm))))

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  1. 1

    A new text-based w-distance metric to find the perfect match between words by Ali, M., Jung, L.T., Hosam, O., Wagan, A.A., Shah, R.A., Khayyat, M.

    Published 2020
    “…The k-NN algorithm is an instance-based learning algorithm which is widely used in the data mining applications. …”
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    Article
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    Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

    Published 2023
    “…Computer aided diagnosis; Data mining; Learning systems; Patient treatment; Predictive analytics; Robotics; Support vector machines; Data mining algorithm; Diabetes mellitus; Early diagnosis; Knowledge accumulation; Literature reviews; Prediction techniques; Review papers; Support vector machine algorithm; Learning algorithms…”
    Conference Paper
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    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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    Thesis
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    Sentiment mining using immune network algorithm /Raja Muhammad Hafiz Raja Kamarudin by Raja Kamarudin, Raja Muhammad Hafiz

    Published 2012
    Subjects: “…Evolutionary programming (Computer science). Genetic algorithms…”
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    Thesis
  7. 7

    Web Usage Mining for UUM Learning Care Using Association Rules by Azizul Azhar, Ramli

    Published 2004
    “…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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    Thesis
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    Web usage mining for UUM learning care using association rules by Ramli, Azizul Azhar

    Published 2004
    “…With the powerful of data mining technique, Web usage mining approach has been combined with the basic Association Rules, Apriori Algorithm to optimize the content of the university E�Learning portal. …”
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    Thesis
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    Accelerated mine blast algorithm for ANFIS training for solving classification problems by Mohd Salleh, Mohd Najib, Hussain, Kashif

    Published 2016
    “…Mine Blast Algorithm (MBA) is newly developed metaheuristic technique. …”
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    Article
  14. 14

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Traditional schema theory does not support Lamatckian learning, i.e, forcing the genetic representation to match the solution found by the learning algorithm. …”
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    Article
  15. 15

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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    Thesis
  16. 16

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

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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    Thesis
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    Dissimilarity algorithm on conceptual graphs to mine text outliers by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2009
    “…The graphical text representation method such as Conceptual Graphs (CGs) attempts to capture the structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the dissimilarity (or similarity) between knowledge represented in the CGs.In this paper, we would like to present a dissimilarity algorithm to detect outliers from a collection of text represented with Conceptual Graph Interchange Format (CGIF).In order to avoid the NP-complete problem of graph matching algorithm, we introduce the use of a standard CG in the dissimilarity computation.We evaluate our method in the context of analyzing real world financial statements for identifying outlying performance indicators.For evaluation purposes, we compare the proposed dissimilarity function with a dice-coefficient similarity function used in a related previous work.Experimental results indicate that our method outperforms the existing method and correlates better to human judgements. …”
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    Conference or Workshop Item
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    Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms by Anuar N.K., Bakar A.A., Ahmad A.R., Yussof S., Rahim F.A., Ramli R., Ismail R.

    Published 2023
    “…Data Analytics; Data mining; Decision making; Feature extraction; Machine learning; Predictive analytics; Privacy by design; Features selection; Fine grains; No leakages; Predictive modeling; Privacy preserving; Learning algorithms…”
    Conference Paper
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    IncSPADE: An Incremental Sequential Pattern Mining Algorithm Based on SPADE Property by Omer, Adam, Zailani, Abdullah, Amir, Ngah, Kasypi, Mokhtar, Wan Muhamad Amir, Wan Ahmad, Herawan, Tutut, Noraziah, Ahmad, Mustafa, Mat Deris, Abdul Razak, Hamdan

    Published 2016
    “…In this paper we propose Incremental Sequential PAttern Discovery using Equivalence classes (IncSPADE) algorithm to mine the dynamic database without the requirement of re-scanning the database again. …”
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    Book Chapter
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    A hybrid serendipity social recommender model / Ahmad Subhi Zolkafly and Rahayu Ahmad by Zolkafly, Ahmad Subhi, Ahmad, Rahayu

    Published 2020
    “…In the next stage, the classification model is used to classify the data into subclasses by using a deep learning algorithm. This algorithm aims to define the higher matching suggested attributes and used for processing massive data. …”
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    Article