**Date**: Friday, 1st December 2017 at 10am

**Place**: LORIA, room B013

**Speaker**: Yves Lepage (Waseda University, Japan)

**Title**: Analogy for natural language processing (NLP) and machine translation (MT)

**Abstract**: In this talk, we introduce the notion of analogy and show its application to language data or to various NLP tasks.

We start from an algebraic definition between vector representations and apply it to pixel images representing Chinese characters. We illustrate a fast algorithm to rapidly structure data into analogical clusters.

By adding the notion of edit distance, we show how to capture analogies between strings of symbols and generalise analogical clusters to analogical grids, a structure similar to paradigm tables in morphology. Such a structure can be used to predict or explain word forms. In particular, we report work on explaining unseen words in Indonesian.

As solving analogical equations between strings of symbols is a key problem to address some tasks like machine translation, we report results on this topic obtained by using standard techniques or neural networks.

We finish by presenting a machine translation system by analogy and sketch future research on it.