Weakly-supervised acquisition of labeled class instances using graph random walks
Published 1 January 2008Open access
Partha Talukdar, Joseph Reisinger, Marius Paşca, Deepak Ravichandran, Rahul Bhagat, Fernando Pereira
Citations133
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TL;DR
This acquisition method significantly improves coverage compared to a previous set of labeled classes and instances derived from free text, while achieving comparable precision.
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.
Keywords
Computer Science
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