Building Trainable Taggers in a Web-based, UIMA-Supported NLP Workbench

Argo is a web-based NLP and text mining workbench with a convenient graphical user interface for designing and executing processing workflows of various complexity. The workbench is intended for specialists and nontechnical audiences alike, and provides the ever expanding library of analytics compliant with the Unstructured Information Management Architecture, a widely adopted interoperability framework. We explore the flexibility of this framework by demonstrating workflows involving three processing components capable of performing self-contained machine learning-based tagging. The three components are responsible for the three distinct tasks of 1) generating observations or features, 2) training a statistical model based on the generated features, and 3) tagging unlabelled data with the model. The learning and tagging components are based on an implementation of conditional random fields (CRF); whereas the feature generation component is an analytic capable of extending basic t...

• Type: Journal
• Year: 2012
• Where: ACL
• Authors: Rafal Rak, BalaKrishna Kolluru, Sophia Ananiadou
• Keywords: ACL 2012, Computational Linguistics, Information Management Architecture, Nontechnical Audiences, Unstructured Information Management Architecture