MUCCA

eMail Unified Content Classification Approach

MUCCA is written in Cincom VisualWorks Smalltalk and is composed of several components.
You can download the source code of the following MUCCA components:

• Miler2, the core of MUCCA, including metamodels, importers, classification engine, etc.;
• MailPeek, our web application for the manual classification of email content;
• PetitIsland, our grammar to generate island parsers;
• PetitJava, the grammar of Java, which we implemented for PetitParser;
• PetitSTrace, our island parser for java stack traces.

Note that, in order to make Miler2 run, you will also need the following external Smalltalk components: Moose, Glorp, Seaside, TwoFlower, MetaDB, PetitParser.

In addition, we make use of the Weka workbench, for the machine learning tasks. You can download the two trained classifiers that compose MUCCA: Naive Bayes based classifier, Decision Tree based classifier.

Alternatively, we created a VirtualBox image with a pre-configured VisualWorks environment, which includes all the MUCCA components, and pre-requisites (both Smalltalk and Java): Download it. (Both user and password are "muccauser").