Comparison of automatic classifiers'performances using word-based feature extraction techniques in an e-government setting

Bachelor thesis English OPEN
Marin Rodenas, Alfonso;
  • Publisher: Kungl. Tekniska högskolan (Estocolm)
  • Subject: Swedish | Computer and Information Sciences | PoStagging | kNN | SVM | machine learning | Administració electrònica | WEKA | e-government | Naive Bayes | feature extraction | automatic e-mail classification | :Informàtica::Sistemes d'informació [Àrees temàtiques de la UPC] | Data- och informationsvetenskap | Internet in public administration | feature selection

Projecte realitzat mitjançant programa de mobilitat. KUNGLIGA TEKNISKA HÖGSKOLAN, STOCKHOLM Nowadays email is commonly used by citizens to establish communication with their government. On the received emails, governments deal with some common queries and subjects wh... View more
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