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Autor*innen: Daxenberger, Johannes; Ferschke, Oliver; Gurevych, Iryna; Zesch, Torsten
Titel: DKPro TC. A Java-based framework for supervised learning experiments on textual data
Aus: Bontcheva, Kalina; Jingbo, Zhu (Hrsg.): Proceedings of COLING 2014: System demonstrations, Stroudsburg; PA: Association for Computational Linguistics, 2014 , S. 61-66
URL: http://aclweb.org/anthology/P/P14/P14-5011.pdf
Dokumenttyp: 4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache: Englisch
Schlagwörter: Automatisierung; Computerlinguistik; Computerprogramm; Data Mining; Datenverarbeitung; Klassifikation; Programmiersprache; Text; Textanalyse
Abstract: 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. (DIPF/Orig.)
DIPF-Abteilung: Informationszentrum Bildung