Public administrations are rapidly advancing towards the provision of basic and extended services for the citizen through the Web (EU eGovernment Report 2014). In addition to the decrement of costs, this effort will support all people’s civil right to have access to all public services (including people with disabilities and elderly people). For this reason the EU started diverse initiatives to “Meeting new societal needs by using emerging technologies in the public sector” in order to “foster efficient, open citizen-centric public services”.

The main goal of the project is the design and development of a system, which implements a process of automatic generation of subtitles for prerecorded video or audio accompanied by an accurate transcription (screenplay). In this project wants develop a prototype. It will be a tool that will offer support for subtitling of audiovisual content in recorded (movies, documentaries, series, etc…) for different media way such as television, Internet and mobile devices.

The aim of this project is to define and develop information extraction and retrieval techniques based on texts from the medical domain. This will be carried out following two basic tasks: firstly, processing scientific documents in English about pharmacology, and secondly, processing informative texts about health topics in other languages such as Spanish and Arabic.

The main purpose of MIRACLE project has been to develop an Information Retrieval system that integrates several techniques and available resources (proceeding from the statistical field as well as from the linguistic technology area) in order to enhance the quality of retrieval in the scope of multilingual information retrieval. This system has been carried out togheter with the Technical University of Madrid and has been succesfuly validated in the CLEF forum (Cross Language Evaluation Forum) in 2003 and 2004 editions.

The aim is to research in technology based on automatic language processing for information location and retrieval from medical texts and other resources (reports, electronic medical records, scientific documentation, etc..) specially in Spanish language. Thus, we worked in browsers with different levels of complexity that integrate medical domain-specific resources and terminology (UMLS, SNOMED, etc.) and with different treatment of syntactic and semantic levels.

BRAVO is devoted to research on technologies to improve the answers search in both text and voice, and the main result is a platform for a modular answers search system which allows to measure the improvement of different techniques for questions classification, answer extraction, passages retrieval, etc. SPINDEL is one of the techniques developed in this project, an entity recognizer which, regardless of language, applies machine learning based on bootstrapping.