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Showing 1 - 5 results of 5 for search '(((( text processing algorithm ) OR ( data modeling algorithm ))) OR ( relevant data algorithm ))~', query time: 0.12s Refine Results
  1. 1
    Cyberbullying Detection Model for Arabic Text Using Deep Learning

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

    Published 2023
    “…The application of DL to cyberbullying detection problems within Arabic text classification can be considered a novel approach due to the complexity of the problem and the tedious process involved, besides the scarcity of relevant research studies.…”
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  2. 2
    Cyberbullying Detection Model for Arabic Text Using Deep Learning

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

    Published 2023
    “…The application of DL to cyberbullying detection problems within Arabic text classification can be considered a novel approach due to the complexity of the problem and the tedious process involved, besides the scarcity of relevant research studies.…”
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  3. 3
    Cyberbullying Detection in Arabic Text using Deep Learning

    Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

    Published 2023
    “…The application of DL to cyberbullying detection problems within Arabic text classification can be considered a novel approach due to the complexity of the problem and the tedious process involved, besides the scarcity of relevant research studies. …”
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  4. 4
    Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study

    Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

    Published 2024
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  5. 5
    Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS

    Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe

    Published 2018
    “…To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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