Efficient Clustering of Emails Into Spam and Ham: The Foundational Study of a Comprehensive Unsupervised Framework.
Asif KarimSami AzamBharanidharan ShanmugamKrishnan KannoorpattiPublished in: IEEE Access (2020)
Keyphrases
- main contribution
- lightweight
- theoretical framework
- theoretical foundation
- statistical analysis
- unsupervised learning
- supervised learning
- clustering method
- empirical studies
- clustering framework
- hierarchical clustering
- information theoretic
- machine learning
- self organizing maps
- fuzzy clustering
- k means
- complexity analysis
- spam filtering
- spam filters
- high dimensional data
- mailing lists
- email spam