Filtering spam in Weibo using ensemble imbalanced classification and knowledge expansion.
Zhipeng JinQiudan LiDaniel ZengLei WangPublished in: ISI (2015)
Keyphrases
- spam e mail
- email spam
- imbalanced data
- training set
- class imbalance
- classification accuracy
- spam detection
- knowledge base
- majority voting
- spam filtering
- decision trees
- feature extraction
- binary classification problems
- feature vectors
- classification models
- domain knowledge
- text classification
- class labels
- anti spam
- feature selection
- benchmark datasets
- spam filters
- ensemble methods
- support vector machine svm
- ensemble learning
- final classification
- imbalanced datasets
- supervised learning
- multiple classifiers
- decision tree classifiers
- high dimensionality
- imbalanced data sets
- classifier combination
- classifier ensemble
- neural network
- machine learning methods
- feature set
- support vector machine
- feature space
- training data
- learning algorithm