Application of Analogical Modelling to Example Based Machine Translation

This paper describes a self-modelling, incremental algorithm for learning translation rules from existing bilingual corpora. The notions of supracontext and subcontext are extended to encompass bilingual information through simultaneous analogy on both source and target sentences and juxtaposition of corresponding results. Analogical modelling is performed during the learning phase and translation patterns are projected in a multi-dimensional analogical network. The proposed fi'amework was evaluated on a small training corpus providing promising results. Suggestions to improve system performance are

• Type: Conference
• Year: 2000
• Where: COLING
• Authors: Christos Malavazosi, Stelios Piperidis
• Keywords: Analogical Modelling, Bilingual Corpora, COLING 2000, COLING 2008, Multi-dimensional Analogical Network