Components for information extraction: ontology-based information extractors and generic platforms

  • Authors:

  • Daya C. Wimalasuriya;Dejing Dou

  • Affiliations:

  • University of Oregon, Eugene, OR, USA;University of Oregon, Eugene, OR, USA

  • Venue:
  • CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
  • Year:
  • 2010

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Abstract

Information Extraction (IE) has existed as a field for several decades and has produced some impressive systems in the recent past. Despite its success, widespread usage and commercialization remain elusive goals for this field. We identify the lack of effective mechanisms for reuse as one major reason behind this situation. Here, we mean not only the reuse of the same IE technique in different situations but also the reuse of information related to the application of IE techniques (e.g., features used for classification). We have developed a comprehensive component-based approach for information extraction that promotes reuse to address this situation. We designed this approach starting from our previous work on the use of multiple ontologies in information extraction [24]. The key ideas of our approach are "information extractors," which are components of an IE system that make extractions with respect to particular components of an ontology and "platforms for IE," which are domain and corpus independent implementations of IE techniques. A case study has shown that this component-based approach can be successfully applied in practical situations.