Exploiting multilingual nomenclatures and language-independent text features as an interlingua for cross-lingual text analysis applications

TL;DR

This paper presents a straightforward, efficient method leveraging multilingual resources and language-independent features to enhance cross-lingual text analysis across many languages with minimal effort.

Contribution

It introduces a novel approach that uses existing multilingual resources and language-independent features for scalable cross-lingual applications.

Findings

Effective for multiple languages without extensive adaptation

Improves cross-lingual document retrieval and clustering

Utilizes existing linguistic resources and language-independent tokens

Abstract

We are proposing a simple, but efficient basic approach for a number of multilingual and cross-lingual language technology applications that are not limited to the usual two or three languages, but that can be applied with relatively little effort to larger sets of languages. The approach consists of using existing multilingual linguistic resources such as thesauri, nomenclatures and gazetteers, as well as exploiting the existence of additional more or less language-independent text items such as dates, currency expressions, numbers, names and cognates. Mapping texts onto the multilingual resources and identifying word token links between texts in different languages are basic ingredients for applications such as cross-lingual document similarity calculation, multilingual clustering and categorisation, cross-lingual document retrieval, and tools to provide cross-lingual information access.