"A Machine Learning Approach for Efficient Spam Detection in Short ..."

Robert G. de Luna et al. (2023)

> Home

Details and statistics

DOI: 10.1109/TENCON58879.2023.10322491

access: closed

type: Conference or Workshop Paper

metadata version: 2024-12-23

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/tencon/LunaMREACELMRR23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/tencon/LunaMREACELMRR23
Robert G. de Luna, Verna C. Magnaye, Rose Anne L. Reaño, Karina L. Enriquez, Dexter Astorga, Trisha M. Celestial, Aira Mae T. Española, Brian Allen Q. Lanting, Danielle M. Mugar, Mateo G. Ramos, Jenjazel M. Redondo:
A Machine Learning Approach for Efficient Spam Detection in Short Messaging System (SMS). TENCON 2023: 53-58

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.