Maurya, Rajesh Kumar. A review of SMS spam detection using features selection. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2022.
A review of SMS spam detection using features selection
Abstract:
Now a days social media is very popular medium for
communication. People used various strategies to communicate
with others. Like email, send message etc. email is very costly
medium for communication with others. So now a days SMS is
the best and effective medium for communication. Because it is
very easy to use. But SMS Spanning problem is increase day by
day. Because people send some illegal message which is very
inconvenient to the users. In this paper we tried to build a
model of detection of the spam message using classification
algorithm along -with feature selection technique. In this paper
we have used Naïve Bayes, Support vector machine, Random
Forest Classifier, and K-Neighbours Classifier . With the help
of these technique, we selected better features that provided
better accuracy. We removed the inappropriate and redundant
attributes that are not valuable for the accuracy of the model.
A comparative study of different algorithm that has been
discussed in literature review is also compared in terms of
Precision, Recall, F1Score, and accuracy
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2022
Modified:
2024-05-14
Issued:
2024-05-14
บทความ/Article
application/pdf
BibliograpyCitation :
In IEEE Computer Society. 2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT 2022) (pp.101-106). Los Alamitos, CA : IEEE Computer Society