David Tomás

Learn More
This paper describes the participation of the University of Alicante (UA) in CLEF 2005 image retrieval task. For this purpose we used an image retrieval system based on probabilistic information combined with ontological information and a feedback technique. Several information streams are created using different sources: stems, words and bigrams; the final(More)
This paper presents the QALL-ME Framework, a reusable architecture for building multi-and cross-lingual Question Answering (QA) systems working on structured data modelled by an ontology. It is released as free open source software with a set of demo components and extensive documentation, which makes it easy to use and adapt. The main characteristics of(More)
As in the previous QA@CLEF track, two separate groups at the University of Ali-cante participated this year using different approaches. This paper describes the work of Alicante 1 group. We have continued with the research line established in the past competition, where the main goal was to obtain a fully data-driven system based on machine learning(More)
This paper describes AliQAn, a monolingual open-domain Question Answering (QA) System developed in the Department of Language Processing and Information Systems at the University of Alicante for CLEF-2005 Spanish monolingual QA evaluation task. Our approach is based fundamentally on the use of syntactic pattern recognition in order to identify possible(More)
This paper describes the novelties introduced in the Question Answering system developed in the Natural Language Processing and Information Systems Group at the University of Alicante for QA@CLEF 2005 campaign with respect to our previous par-ticipations. Thinking of future developments, this year we have designed a modular framework based on XML that will(More)
This article presents a minimally supervised approach to question classification on fine-grained taxonomies. We have defined an algorithm that automatically obtains lists of weighted terms for each class in the taxonomy, thus identifying which terms are highly related to the classes and are highly discriminative between them. These lists have then been(More)
This paper presents the QALL-ME benchmark, a multilingual resource of annotated spoken requests in the tourism domain, freely available for research purposes. The languages currently involved in the project are Italian, English, Spanish and German. It introduces a semantic annotation scheme for spoken information access requests, specifically derived from(More)
On-line Social Networks have increased their popularity rapidly since their creation, providing a huge amount of data which can be leverage to extract useful information related to commercial and social human behaviours. One of the most useful information that can be extracted is the geographical one. This paper shows an approach to detect the geographical(More)