Weakly-supervised acquisition of labeled class instances using graph random walks

Authors:
Partha Pratim Talukdar;Joseph Reisinger;Marius Paşca;Deepak Ravichandran;Rahul Bhagat;Fernando Pereira
Affiliations:
University of Pennsylvania, Philadelphia, PA;University of Texas at Austin, Austin, TX;Google Inc., Mountain View, CA;Google Inc., Mountain View, CA;USC Information Sciences Institute, Marina Del Rey, CA;Google Inc., Mountain View, CA
Venue:
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Year:
2008

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Abstract

We present a graph-based semi-supervised label propagation algorithm for acquiring open-domain labeled classes and their instances from a combination of unstructured and structured text sources. This acquisition method significantly improves coverage compared to a previous set of labeled classes and instances derived from free text, while achieving comparable precision.