Výsledky vyhľadávania - LSTM and SVM NLP Machine learning Transformer SVM offensive language

  • Zobrazené výsledky 1 - 4 z 4
Upresniť hľadanie
  1. 1

    Arabic Offensive Language Classification: Leveraging Transformer, LSTM, and SVM Autor Rasheed, Areeg Fahad, Zarkoosh, M., Abbas, Safa F., Sabah Al-Azzawi, Sana

    ISBN: 9798350303926, 9798350303919
    Vydavateľské údaje: IEEE 14.12.2023
    “… Three distinct strategies were used: support vector machine (SVM), long short-term memory (LSTM…”
    Získať plný text
    Konferenčný príspevok..
  2. 2

    RU-OLD: A Comprehensive Analysis of Offensive Language Detection in Roman Urdu Using Hybrid Machine Learning, Deep Learning, and Transformer Models Autor Zain, Muhammad, Hussain, Nisar, Qasim, Amna, Mehak, Gull, Ahmad, Fiaz, Sidorov, Grigori, Gelbukh, Alexander

    ISSN: 1999-4893, 1999-4893
    Vydavateľské údaje: Basel MDPI AG 01.07.2025
    Vydané v Algorithms (01.07.2025)
    “… This work investigates machine learning (ML), deep learning (DL), and transformer-based methods for detecting offensive language in Roman Urdu comments collected from YouTube news channels…”
    Získať plný text
    Journal Article
  3. 3

    NLP-CUET@DravidianLangTech-EACL2021: Offensive Language Detection from Multilingual Code-Mixed Text using Transformers Autor Sharif, Omar, Hossain, Eftekhar, Hoque, Mohammed Moshiul

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 28.02.2021
    Vydané v arXiv.org (28.02.2021)
    “… To accomplish the tasks, we employed two machine learning techniques (LR, SVM), three deep learning (LSTM, LSTM+Attention…”
    Získať plný text
    Paper
  4. 4

    Detection of Inappropriate Language on Social Media Platforms Using Machine Learning Algorithms Autor Mishra, Shri Om, Ahmer, Mohd, Mittal, Nupur, Maurya, Akhilesh Kumar, Kumar Singh, Amit, Kumar, Ashawani

    ISBN: 9798350364682
    Vydavateľské údaje: IEEE 15.11.2024
    “… This paper explores the effectiveness of different machine learning techniques in detecting offensive language on social media, using real-world datasets…”
    Získať plný text
    Konferenčný príspevok..