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jTCat (java Text Categorization) is a tool for Text Categorization. It is based on a supervised machine learning approach. In particular, jTCat uses a combination of kernel functions to embed the original feature space in a low dimensional one. jTCat requires only a shallow linguistic processing, such as tokenization, part-of-speech tagging (optional) tagging and lemmatization (optional).
Some of jTCat's features include:
- Implements the latent semantic kernel
- Written in Java
- Supports user-defined data representation and kernel functions
jTCat is developed by Claudio Giuliano.
jTCat is freely available for research purposes; in order to obtain a license, please contact Claudio Giuliano.