David Tomás

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This paper presents the QALL-ME Framework, a reusable architecture for building multiand 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 the(More)
As in the previous QA@CLEF track, two separate groups at the University of Alicante 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 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 participations. Thinking of future developments, this year we have designed a modular framework based on XML that will(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)
The geographical focus of a document identifies the relevant locations mentioned in text. This paper presents a corpus-based approach to detecting the geographical focus in documents. Despite other approaches focused on using solely geographical information, our proposal employs all the textual information included in the corpus under the assumption that(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)