Showing 1 - 7 results of 7 for search '(( relevant data algorithm ) OR ((( data finding algorithm ) OR ( data modeling algorithm ))))~', query time: 0.07s Refine Results
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    Indexing Arabic texts using association rule data mining by Haraty, Ramzi A.

    Published 2019
    “…Purpose The purpose of this paper is to propose a new model to enhance auto-indexing Arabic texts. The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. …”
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    C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments by Raun, Kristo

    Published 2023
    “…The aim of streaming conformance checking is to find dis crepancies between process executions on streaming data and the refer ence process model. …”
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  4. 4

    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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    A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis by Alaa Abd-Alrazaq (17430900)

    Published 2021
    “…Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.…”
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    Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

    Published 2023
    “…In this study, I conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM, CNN-BILSTM-LSTM, and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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