Search Results - (( java application using algorithm ) OR ( a solution ((mining algorithm) OR (means algorithm)) ))

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  1. 1
    A modified π rough k-means algorithm for web page recommendation system

    A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

    Published 2018
    “…Secondly, a modified πRKM algorithm is proposed to partition the user session data. …”
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  2. 2
    A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works

    A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

    Published 2023
    Conference Paper
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  3. 3
    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
    Article
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  4. 4
    Profiling network traffic of Sultan Idris Shah building (BSIS) using data mining technique / Rusmawati Ishak

    Profiling network traffic of Sultan Idris Shah building (BSIS) using data mining technique / Rusmawati Ishak by Ishak, Rusmawati

    Published 2018
    “…Orange is a tool that being used in implementing K-Means Clustering Algorithm that could be seen as the most suitable solution to find a network trend pattern of user accessing the Internet and to produce with profiling network. …”
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  5. 5
    Towards a better feature subset selection approach

    Towards a better feature subset selection approach by Shiba, Omar A. A.

    Published 2010
    “…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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  6. 6
    Tacit knowledge for business intelligence framework using cognitive-based approach

    Tacit knowledge for business intelligence framework using cognitive-based approach by Surbakti, Herison

    Published 2022
    “…The framework was tested on 23 librarians from several university libraries in West Java and Yogyakarta, Indonesia. The algorithm starts with a content targeted interview to identify the list of problems faced by librarians. …”
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  7. 7
    Fuzzy Soft Set Clustering for Categorical Data

    Fuzzy Soft Set Clustering for Categorical Data by Iwan Tri Riyadi, Yanto, Ani, Apriani, Rofiul, Wahyudi, Cheah, Wai Shiang, Suprihatin, in, Rahmat, Hidayat

    Published 2024
    “…This involves producing a multi-soft set by using a rotated based soft set, and then clustering the data using a multivariate multinomial distribution. …”
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  8. 8
    A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution

    A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution by Abdulrazak Yahya, Saleh, Haza Nuzly, Abdull Hamed, Siti Mariyam, Shamsuddin, Ashraf, Osman Ibrahim

    Published 2018
    “…This approach improves the flexibility of the ESNN algorithm in producing better solutions which is utilized to conquer the K-means disadvantages. …”
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  9. 9
    Mine blast algorithm for optimization of truss structures with discrete variables

    Mine blast algorithm for optimization of truss structures with discrete variables by Sadollah, Ali, Bahreininejad, A., Eskandar, Hadi, Abd Shukor, Mohd Hamdi

    Published 2012
    “…In this study a novel optimization method is presented, the so called mine blast algorithm (MBA). …”
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  10. 10
    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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  11. 11
    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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  12. 12
    A numerical method for frequent pattern mining

    A numerical method for frequent pattern mining by Mustapha, Norwati, Nadimi-Shahraki, Mohammad-Hossein, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2009
    “…There are two new properties introduced in this method; a novel tree structure called PC_Tree and PC_Miner algorithm. …”
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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
    A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi

    A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi by Nassirtoussi, Arman Khadjeh

    Published 2015
    “…The algorithm tackles a different root cause of the problem at each layer. …”
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  15. 15
    Towards scalable algorithm for closed itemset mining in high-dimensional data

    Towards scalable algorithm for closed itemset mining in high-dimensional data by Md. Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza

    Published 2017
    “…Mining frequent itemsets from large dataset has a major drawback in which the explosive number of itemsets requires additional mining process which might filter the interesting ones. …”
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  16. 16
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
    “…Traditional data mining algorithms cannot be directly applied to educational problems, as they may have a specific objective and function. …”
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  17. 17
    A Stochastic Total Least Squares Solution of Adaptive Filtering Problem

    A Stochastic Total Least Squares Solution of Adaptive Filtering Problem by Javed, Shazia, Ahmad, Noor Atinah

    Published 2014
    “…The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. …”
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  18. 18
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Mining contrast subspace finds subsets of features or subspaces where a query object is most likely similar to target class against other class in a multidimensional data set of two classes. …”
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  19. 19
    Using unique-prime-factorization theorem to mine frequent patterns without generating tree

    Using unique-prime-factorization theorem to mine frequent patterns without generating tree by Tohidi, Hossein, Ibrahim, Hamidah

    Published 2011
    “…For huge database it may need to generate a huge number of candidate sets. An interest solution is to design an approach that without generating candidate is able to mine frequent patterns. …”
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  20. 20
    Machine Learning Algorithms for Diabetes Prediction: A Review Paper

    Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

    Published 2023
    Conference Paper
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