A Robust Approach to Aligning Heterogeneous Lexical Resources
Mohammad Taher Pilehvar, Roberto Navigli · 2014
Lexical resource alignment has been an active field of research over the last decade. However, prior methods for align-ing lexical resources have been either spe-cific to a particular pair of resources, or heavily dependent on the availability of hand-crafted alignment data for the pair of resources to be aligned. Here we present a unified approach that can be applied to an arbitrary pair of lexical resources, includ-ing machine-readable dictionaries with no network structure. Our approach leverages a similarity measure that enables the struc-tural comparison of senses across lexical resources, achieving state-of-the-art per-formance on the task of aligning WordNet to three different collaborative resources: Wikipedia, Wiktionary and OmegaWiki. 1