000K  utf8
1100  $c2014
1500  eng
2050  urn:nbn:de:hbz:464-20211026-130458-0
2051  10.3115/v1/P14-5011
3000  Daxenberger, Johannes
3010  Ferschke, Oliver
3010  Gurevych, Iryna
3010  Zesch, Torsten
4000  DKPro TC: A Java-based Framework for Supervised Learning Experiments on Textual Data  [Daxenberger, Johannes]
4209  We present DKPro TC, a framework for supervised learning experiments on textual data. The main goal of DKPro TC is to enable researchers to focus on the actual research task behind the learning problem and let the framework handle the rest. It enables rapid prototyping of experiments by relying on an easy-to-use workflow engine and standardized document preprocessing based on the Apache Unstructured Information Management Architecture (Ferrucci and Lally, 2004). It ships with standard feature extraction modules, while at the same time allowing the user to add customized extractors. The extensive reporting and logging facilities make DKPro TC experiments fully replicable.
4950  https://doi.org/10.3115/v1/P14-5011$xR$3Volltext$534
4950  https://nbn-resolving.org/urn:nbn:de:hbz:464-20211026-130458-0$xR$3Volltext$534
4961  https://duepublico2.uni-due.de/receive/duepublico_mods_00072167
5051  004