Nonlinear Evidence Fusion and Propagation for Hyponymy Relation Mining.

This paper focuses on mining the hyponymy (or is-a) relation from large-scale, open-domain web documents. A nonlinear probabilistic model is exploited to model the correlation between sentences in the aggregation of pattern matching results. Based on the model, we design a set of evidence combination and propagation algorithms. These significantly improve the result quality of existing approaches. Experimental results conducted on 500 million web pages and hypernym labels for 300 terms show over 20% performance improvement in terms of P@5, MAP and R-Precision.