Paper: Graph-based Analysis of Semantic Drift in Espresso-like Bootstrapping Algorithms

ACL ID D08-1106
Title Graph-based Analysis of Semantic Drift in Espresso-like Bootstrapping Algorithms
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008
Authors

Bootstrapping has a tendency, called seman- tic drift, to select instances unrelated to the seed instances as the iteration proceeds. We demonstrate the semantic drift of bootstrap- ping has the same root as the topic drift of Kleinberg’s HITS, using a simplified graph- based reformulation of bootstrapping. We confirm that two graph-based algorithms, the von Neumann kernels and the regularized Laplacian, can reduce semantic drift in the task of word sense disambiguation (WSD) on Senseval-3 English Lexical Sample Task. Proposed algorithms achieve superior perfor- mance to Espresso and previous graph-based WSD methods, even though the proposed al- gorithms have less parameters and are easy to calibrate.