Marta Villegas

Cross-lingual text categorization

This article deals with the problem of Cross-Lingual Text Categorization (CLTC), which arises when documents in different languages must be classified according to the same classification tree. We describe practical and cost-effective solutions for automatic Cross-Lingual Text Categorization, both in case a sufficient number of training examples is available for each new language and in the case that for some language no training examples are available.

One Ontology to Bind Them All: The META-SHARE OWL Ontology for the Interoperability of Linguistic Datasets on the Web

META-SHARE is an infrastructure for sharing Language Resources LRs where significant effort has been made into providing carefully curated metadata about LRs. However, in the face of the flood of data that is used in computational linguistics, a manual approach cannot suffice. We present the development of the META-SHARE ontology, which transforms the metadata schema used by META-SHARE into ontology in the Web Ontology Language OWL that can better handle the diversity of metadata found in legacy and crowd-sourced resources. We show how this model can interface with other more general purpose vocabularies for online datasets and licensing, and apply this model to the CLARIN VLO, a large source of legacy metadata about LRs. Furthermore, we demonstrate the usefulness of this approach in two public metadata portals for information about language resources.

The apertium bilingual dictionaries on the web of data

Bilingual electronic dictionaries contain collections of lexical entries in two languages, with explicitly declared translation relations between such entries. Nevertheless, they are typically developed in isolation, in their own formats and accessible through proprietary APIs. In this paper we propose the use of Semantic Web techniques to make translations available on the Web to be consumed by other semantic enabled resources in a direct manner, based on standard languages and query means. In particular, we describe the conversion of the Apertium family of bilingual dictionaries and lexicons into RDF (Resource Description Framework) and how their data have been made accessible on the Web as linked data. As a result, all the converted dictionaries (many of them covering under-resourced languages) are connected among them and can be easily traversed from one to another to obtain, for instance, translations between language pairs not originally connected in any of the original dictionaries.

The CLARIN project: a scientific research infrastructure for the humanities and social sciences

This article presents the CLARIN (Common Language Resources and Technologies) project, a large-scale pan-European collaborative project that aims to promote the use of technological tools in research in the fields of the humanities and social sciences. CLARIN is one of the 35 projects selected by ESFRI (European Strategy Forum on Research Infrastructures) to form a list of infrastructures that need to be built, due to their importance in terms of research, in the next ten years. CLARIN aims to bring the benefits of shared and collaborative access to digital resources to the humanities and social sciences and increase use of specific analysis and exploitation computing tools for intelligent access to large databases. With this in mind, CLARIN is to create the infrastructure needed to offer generic access to large databases, alongside technological tools for the analysis and exploitation of the data. To do so, the project envisions a grid structure using web service and semantic web technologies, a single interface for accessing data and analysis tools, as well as the processing tools and other services needed. This interface, due to the fact that is designed to meet the common research aims in the humanities and social sciences, is easy to use by researchers from different fields without any prior knowledge of the technology involved.