Applying word embeddings to leverage knowledge available in one language in order to solve a practical text classification problem in another language

Abstract

A text classification problem in Kazakh language is examined. The amount of training data for the task in Kazakh is very limited, but plenty of labeled data in Russian are available. Language vector space transform is built and used to transfer knowledge from Russian into Kazakh language. The obtained classification quality is comparable to that of an approach that employed sophisticated automatic translation system.