MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
Designing and refining ontologies becomes a tedious task, once the boundary to real-world-size knowledge bases has been crossed. Hence semi-automatic methods supporting those tasks will determine the future success of ontologies in practice. Our research therefore aims at the conceptual development and implementation of tools for semi-automatic ontology engineering. By combining Ontology Learning and Relational Exploration we hope to overcome the knowledge acquisition bottleneck, especially with respect to expressive axiomatizations (see our seminal paper at ICCS'2007). The RELExO framework supporting the refinement and evaluation of OWL DL ontologies is open source and publicly available under the LGPL license.
N. Abe, and R. Khardon (Eds.) Elsevier Science Publishers B.V., Amsterdam, (2004)Papers from the 12th Annual Conference (ALT'01) held in Washington, DC, November 25--28, 2001, Theoret. Comput. Sci. 313 (2004), no. 2.
S. Rudolph, J. Völker, and P. Hitzler. Conceptual Structures: Knowledge Architectures for Smart Applications, Proc. ICCS 2007, volume 4604 of LNAI, page 488-491. Sheffield, UK, Springer, (July 2008)ISBN: 978-3-540-73680-6
ISSN: 0302-9743.