jTCat

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.