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  • تعديل
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    , Vol. , No. , pp. ,
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  • تعديل Convolutional neural network for automatic identification of plant diseases with limited data
    Ahmed Afifi,Abdulaziz Alhumam, and Amira Abdelwahab
    Plants, Vol. 10, No. 1, pp. 28, 2020
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  • تعديل A Proposed Framework for Improving Analysis of Big Unstructured Data in Social Media
    Amira Abdelwahab,Mohamed Elsayed, Hatem Ahdelkader
    14th International conference on computer engineering and systems (ICCES), Vol. , No. , pp. 61-65, 2019
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  • تعديل An analytic framework for enhancing the performance of big heterogeneous data analysis
    Amira Abdelwahab,Mohamed Salama, Hatem Abdul Kader
    International Journal of Engineering Business Management, Vol. 13, No. , pp. , 2021
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  • تعديل Detecting spam campaign in twitter with semantic similarity
    Amira Abdelwahab,Mohamed Mostafa, HM Sayed
    Journal of physics: conference series, Vol. 1447, No. 1, pp. , 2020
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  • تعديل Enhancing the performance of sentiment analysis supervised learning using sentiments keywords based technique
    Amira Abdelwahab,Fahd Alqasemi, Hatem Abdelkader
    CS & IT Conference Proceedings, Vol. 7, No. 1, pp. , 2017
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  • تعديل Evaluating Non-redundant Rules of Various Sequential Rule Mining Algorithms
    Amira Abdelwahab,Nesma Youssef, Hatem Abdulkader
    International Conference on Advanced Intelligent Systems and Informatics, Vol. , No. , pp. 429-440, 2020
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  • تعديل Mining frequent sequential rules with an efficient parallel algorithm
    Amira Abdelwahab,Nesma Youssef, Hatem Abdul-Kader
    Int. Arab J. Inf. Technol, Vol. 19, No. 1, pp. 110-120, 2022
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  • تعديل Deep Learning Models for Heterogeneous Big Data Analytics
    Amira Abdelwahab,Mohamed Elsayed, Hatem Abdelkader
    15th International Conference on Computer Engineering and Systems (ICCES), Vol. , No. , pp. 1-5, 2020
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  • تعديل Event Detection Based on Semantic Terms from Social Data Stream
    Amira Abdelwahab,Ahmed Gamal, Hatem Abdelkader
    Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA, Vol. , No. , pp. 478-487, 2021
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