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 main project purpose is the design and development of a set of software tools to support Software Engineering Best Practices, defined by international standardization organizations such as ISO, SEI and PMI. These tools will allow the definition of software processes and will assist in the software project management based on Best Practices Models.

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.

MAVIR Consortium is a research network co-funded by the Regional Government of Madrid under the IV Plan Regional de Investigación Científica e Innovación Tecnológica (IV PRICIT) integrating a multi-disciplinar team made of scientists, engineers, linguists and documentalists working together on two main areas:Human Language Technologies and Scientific Communication via WWW. The thematic network suggested includes 25 doctors organised in 6 research groups (UNED, UAM, UC3M, UEM, UPM and CINDOC) of the CM that from a multi-discipline perspective complement in various dimensions: academic vs.

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.