Automatic Bilingual Lexicon Acquisition Using Random Indexing of Aligned Bilingual Data
Swedish Institute of Computer Science, SICS
This paper presents a very simple and effective approach to automatic bilingual lexicon acquisition. The approach is cooccurrence-based, and uses the Random Indexing vector space methodology applied to aligned bilingual data. The approach is simple, efficient and scalable, and generate promising results when compared to a manually compiled lexicon. The paper also discusses some of the methodological problems with the prefered evaluation procedure.
Terminology, lexicon acquisition, vector space model, random indexing.