Paper: Weakly-Supervised Acquisition of Labeled Class Instances using Graph Random Walks

ACL ID D08-1061
Title Weakly-Supervised Acquisition of Labeled Class Instances using Graph Random Walks
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008
Authors

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