Search alternatives:
processing algorithm » processing algorithms (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
Showing 21 - 40 results of 92 for search '(( element data algorithm ) OR ((( text processing algorithm ) OR ( neural fitting algorithm ))))', query time: 0.13s Refine Results
  1. 21
  2. 22
  3. 23

    A feature‐based approach for guiding the selection of Internet of Things cybersecurity standards using text mining by Koen Schaaf (14778139)

    Published 2021
    “…Second, an up-to-date overview of the IoT cybersecurity standards landscape has been mapped by combining existing overviews. Third, a text mining algorithm has been implemented. Fourth, the systematic approach has been modeled using business process modeling notation. …”
  4. 24

    Fast Text Classification using Lean Gradient Descent Feed Forward Neural Network for Category Feature Augmentation by Attieh, Joseph

    Published 2024
    “…Text classification is a key task of the Natural Language Processing (NLP) field that aims at assigning predefined categories to textual documents. …”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject
  5. 25

    Particle swarm optimization algorithm: review and applications by Abualigah, Laith

    Published 2024
    “…This paper surveys the published papers in PSO algorithms. Twenty research papers are analyzed and classified according to the implementation area used by the PSO algorithm (neural networks, feature selection, and data clustering). …”
    Get full text
  6. 26
  7. 27
  8. 28
  9. 29
  10. 30
  11. 31
  12. 32
  13. 33
  14. 34

    A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques by SALLOUM, SAID

    Published 2022
    “…We study the key research areas in phishing email detection using NLP, machine learning algorithms used in phishing detection email, text features in phishing emails, datasets and resources that have been used in phishing emails, and the evaluation criteria. …”
    Get full text
    Get full text
  15. 35

    Sentiment analysis for Arabizi in social media. (c2015) by Tobaili, Taha

    Published 2015
    “…Informal Arabic lacks standardization and has no grammar, thus sentimental analysis in this area is considered a complex process. Sentiment Analysis for Arabic has been studied for MSA (Modern Standard Arabic) but rarely for informal Arabic, and non-existent for Arabizi; whereas most of the youth in Lebanon text in Arabizi claiming that it is easier than texting in Arabic. …”
    Get full text
    Get full text
    masterThesis
  16. 36

    An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

    Published 2015
    “…The huge amounts of data generated by media sensors in health monitoring systems, by medical diagnosis that produce media (audio, video, image, and text) content, and from health service providers are too complex and voluminous to be processed and analyzed by traditional methods. …”
    Get full text
    Get full text
    Get full text
    Get full text
    article
  17. 37
  18. 38
  19. 39

    Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic by AL MANSOORI, MOUZA

    Published 2021
    “…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. In this study, we used twitter as our data source. …”
    Get full text
  20. 40

    XBeGene: Scalable XML Documents Generator by Example Based on Real Data by Harazaki, Manami

    Published 2012
    “…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject