Location of Repository

Refining Information Extraction Rules using Data Provenance

By Bin Liu

Abstract

Developing high-quality information extraction (IE) rules, or extractors, is an iterative and primarily manual process, extremely time consuming, and error prone. In each iteration, the outputs of the extractor are examined, and the erroneous ones are used to drive the refinement of the extractor in the next iteration. Data provenance explains the origins of an output data, and how it has been transformed through a query. As such, one can expect data provenance to be valuable in understanding and debugging complex IE rules. In this paper we discuss how data provenance can be used beyond understanding and debugging, to automatically refine IE rules. In particular, we overview the main ideas behind a recent provenance-based solution for suggesting a ranked list of refinements to an extractor aimed at increasing its precision, and outline several related directions for future research.

Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.187.1675
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://sites.computer.org/debu... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.