SMS CLASSIFICATION BASED ON NAIVE BAYES CLASSIFIER AND SEMI-SUPERVISED LEARNING
| Main Author: | PROF. P.N. KALAVADEKAR |
|---|---|
| Format: | Article Journal |
| Bahasa: | eng |
| Terbitan: |
, 2016
|
| Subjects: | |
| Online Access: |
https://zenodo.org/record/1462689 |
Daftar Isi:
- Short Message Service is one of the most important media of communication due to the rapid increase of mobile users. A hybrid system of SMS classification is used to detect spamor ha m,using various algorithms such as Na�ve Bayes classifier and Apriori Algorithm. So there is needed to perform SMS collection,feature selection,pre - processing,vector creation,filtering process and updating system. Two types of SMS classification exist s in current mobile phone and they are enlisted as Black and White. Na�ve Bayes is considered as one of the most effectual and significant learning algorithms for data mining and machine learning and also has been treated as a core technique in information retrieval. https://www.ijiert.org/paper-details?paper_id=140926