Comparing Manual Text Patterns and Machine Learning for Classification of E-Mails for Automatic Answering by a Government Agency.
Hercules DalianisJonas SjöberghEriks SneidersPublished in: CICLing (2) (2011)
Keyphrases
- machine learning
- supervised machine learning
- pattern recognition
- semi automatic
- decision trees
- text classification
- feature selection
- text mining
- machine learning methods
- machine learning algorithms
- pattern analysis
- supervised learning
- lung disease
- statistical classification
- classification method
- classification accuracy
- support vector machine
- feature vectors
- data mining techniques
- support vector
- information retrieval
- government agencies
- data mining
- spam filtering
- information technology
- pattern mining
- neural network
- united states
- labor intensive
- manual annotation
- classification models
- classification rules
- learning algorithm
- feature extraction
- feature space
- natural language processing
- fully automatic
- classification algorithm
- support vector machine svm
- text categorization
- machine learning approaches
- model selection
- data analysis
- semi supervised
- active learning
- pattern representation