A statistical approach to crosslingual natural language tasks

The existence of huge volumes of documents written in multiple languages in Internet lead to investigate novel approaches to deal with information of this kind. We propose to use a statistical approach in order to tackle the problem of dealing with crosslingual natural language tasks. In particular, we apply the IBM alignment model 1 with the aim of obtaining a statistical bilingual dictionary which may further be used in order to approximate the relatedness probability of two given documents (written in different languages). The experimental results sucessfully obtained in three different tasks –text classification, information retrieval and plagiarism analysis– highlight the benefit of using the presented statistical approach.