Paper: DKPro TC: A Java-based Framework for Supervised Learning Experiments on Textual Data

ACL ID P14-5011
Title DKPro TC: A Java-based Framework for Supervised Learning Experiments on Textual Data
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

We present DKPro TC, a framework for supervised learning experiments on tex- tual data. The main goal of DKPro TC is to enable researchers to focus on the actual research task behind the learning problem and let the framework handle the rest. It enables rapid prototyping of experiments by relying on an easy-to-use workflow en- gine and standardized document prepro- cessing based on the Apache Unstruc- tured Information Management Architec- ture (Ferrucci and Lally, 2004). It ships with standard feature extraction modules, while at the same time allowing the user to add customized extractors. The exten- sive reporting and logging facilities make DKPro TC experiments fully replicable.