In this post, I want to show how I use NLTK for preprocessing and tokenization, but then apply machine learning techniques (e.g. building a linear SVM using stochastic gradient descent) using Scikit-Learn.
@startuml
participant User
User -> A: DoWork
activate A #FFBBBB
A -> A: Internal call
activate A #DarkSalmon
A -> B: << createRequest >>
activate B
B --> A: RequestCreated
deactivate B
deactivate A
A -> User: Done
deactivate A
@enduml
K. Brinker, G. Antos, W. Heinemann, and S. Sager (Eds.).
. Handbücher zur Sprach- und Kommunikationswissenschaft / Handbooks of Linguistics and Communication Science de Gruyter, Berlin, (2000)
C. Henning, and R. Ewerth. Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval, page 14--22. New York, NY, USA, ACM, (2017)
G. Barbieri, F. Pachet, P. Roy, and M. Esposti. Proceedings of the 20th European Conference on Artificial Intelligence, page 115--120. Amsterdam, The Netherlands, The Netherlands, IOS Press, (2012)