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英文字典中文字典相关资料:


  • Comparative Analysis of Natural Language Processing Models for Malware . . .
    Comparative Analysis of Natural Language Processing Models for Malware Spam Email Identification Francisco Jáñez-Martino, Eduardo Fidalgo, Rocío Alaiz-Rodríguez, Andrés Carofilis, Alicia Martínez-Mendoza Use this form to create a GitHub issue with structured data describing the correction You will need a GitHub account
  • Natural Language Processing in Email Spam Filtering: A Comparative . . .
    This research examines the application of natural language processing (NLP) techniques to improve email classification, focusing on effectively identifying spam and ham (legitimate) emails Given the growing risks spam emails present to cybersecurity and
  • Next-Generation Spam Filtering: Comparative Fine-Tuning of LLMs . . . - MDPI
    By integrating cutting-edge NLP and LLM models into spam filtering mechanisms and fine-tuning them with few-shot learning for this specific task, our research endeavors to contribute to the advancement of email security frameworks and mitigate the evolving threats posed by spam and phishing attacks
  • Comparative Analysis and Optimization of Spam Filtration Techniques . . .
    Spam emails, messages, and content remain a persistent nuisance in the digital landscape, demanding effective and efficient classification methods This paper presents an exploration of several techniques for spam classification using Natural Language Processing (NLP) techniques, we aimed to optimize the performance of spam filtration algorithms Through rigorous experimentation and analysis
  • Proceedings of the 1st International Conference on NLP . . . - ACL Anthology
    Session 3: Spam and phishing (Session Chair: Lena Podoletz) Comparative Analysis of Natural Language Processing Models for Malware Spam Email Identification Francisco Jáñez-Martino, Eduardo Fidalgo, Rocío Alaiz-Rodríguez, Andrés Caro-filis, and Alicia Martínez-Mendozaxii
  • Machine learning algorithm for detecting suspicious email messages . . .
    The main point of this research was the identification of potentially valuable email header features for enhancing email spam detection To accomplish this objective, the researchers conducted a meticulous analysis of two distinct email datasets, namely the Anomaly Detection Challenges dataset and the Cybersecurity Data Mining dataset, both
  • International Conference on Natural Language Processing and Artificial . . .
    Comparative Analysis of Natural Language Processing Models for Malware Spam Email Identification Francisco Jáñez-Martino | Eduardo Fidalgo | Rocío Alaiz-Rodríguez | Andrés Carofilis | Alicia Martínez-Mendoza
  • A Comparative Analysis of Count-Based and Inference-Based NLP Models in . . .
    In the era of digital communication, distinguishing spam from legitimate emails has become a crucial task This study provides a comparative analysis of count-based and inference-based Natural Language Processing (NLP) models in spam email detection Focusing on the TFIDF-SVD-RF model and the Word2Vec-BiGRU-NN model, the research utilizes a real-life email dataset The count-based model
  • ACL Anthology
    The ACL Anthology is a library of publications in the scientific fields of computational linguistics and speech and natural language processing It currently hosts 122,130 papers from official venues of the Association for Computational Linguistics and other organizations
  • Spam email classification based on cybersecurity potential risk using . . .
    To assess the potential risk of spam emails for users, we follow two strategies: a binary classification using low and high risk and a regression approach to predict the level of risk from 1 to 10 We evaluated three Machine Learning classifiers and three regression models





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