Abstract
In this digital world, most of the communication is done only through the Internet. Email is widely used for exchanging information not only for personal communication but also has an important part in business communication because of its effectiveness, fastness, and cost-effective mode of communication. Spam email is the serious problem on the Internet; when users click on to the spam mail, it starts spreading viruses in the user system, consumes lot of network bandwidth and email storage space, and steals user’s confidential data. Feature selection approach selects the best features from the dataset which removes irrelevant, redundant, and noisy data. The proposed paper offers email spam detection which incorporates various feature selection approaches like Information Gain, Correlation-Based Feature Selection, Genetic Algorithm, Ant Colony Optimization, Artificial Bee Colony, Particle Swarm Optimization, Cuckoo Search Algorithm, Harmony Search Algorithm, etc.; when classification is done after feature selection, it will enhance the performance of spam filtering.
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Abbreviations
- ABC:
-
Artificial Bee Colony Optimization
- BoW:
-
Bag-of-Word
- CGA:
-
Compact Genetic Algorithm
- EA:
-
Evolutionary Algorithm
- F-GSO:
-
Firefly-Group Search Optimizer
- HKSVM:
-
Hybrid Kernel based Support Vector Machine
- HSA:
-
Harmony Search Algorithm
- KNN:
-
K-Nearest Neighbors
- LR:
-
Logistic Regression
- MLP:
-
Multi-Layer Perceptron
- MLP-NN:
-
Multi-Layer Perceptron Neural Network
- NB:
-
Naïve Bayes
- PCA:
-
Principal Component Analysis
- PNN:
-
Probabilistic Neural Network
- PoS:
-
Part-of-Speech
- PSO:
-
Particle Swarm Optimization
- PU:
-
Positive Unlabeled
- RF:
-
Random Forests
- SCS:
-
Stepsize Cuckoo Search
- SMO:
-
Sequential Minimal Optimization
- SVM:
-
Support Vector Machine
- TF-IDF:
-
Term Frequency – Inverse Document Frequency
- TREC:
-
Text Retrieval Conference
- UCI:
-
UC Irvine
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Acknowledgments
Our sincere thanks to the University Grants Commission (UGC), Hyderabad, for granting the funds to carry out this work.
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Vinitha, V.S., Renuka, D.K. (2020). Feature Selection Techniques for Email Spam Classification: A Survey. In: Kumar, L., Jayashree, L., Manimegalai, R. (eds) Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications. AISGSC 2019 2019. Springer, Cham. https://doi.org/10.1007/978-3-030-24051-6_86
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DOI: https://doi.org/10.1007/978-3-030-24051-6_86
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