José Luis Martínez-Fernández

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The main goal of the bilingual and monolingual participation of the MIRACLE team in CLEF 2004 was to test the effect of combination approaches on information retrieval. The starting point was a set of basic components: stemming, transformation, filtering, generation of n-grams, weighting and relevance feedback. Some of these basic components were used in(More)
ImageCLEF is a pilot experiment run at CLEF 2003 for cross language image retrieval using textual captions related to image contents. In this paper, we describe the participation of the MIRACLE research team (Multilingual Information RetrievAl at CLEF), detailing the different experiments and discussing their preliminary results.
This paper presents the image retrieval techniques tested by the MIRACLE (Multilingual Information RetrievAl for the CLEf campaign) research group as part of the ImageCLEF 2004 initiative. Two main lines of research continuing the past year's experiments were considered: the application of linguistic techniques to improve retrieval performance and the(More)
This paper describes the first set of experiments defined by the MIRACLE (Multilingual Information RetrievAl for the CLEf campaign) research group for some of the cross language tasks defined by CLEF. These experiments combine different basic techniques, linguistic-oriented and statistic-oriented, to be applied to the indexing and retrieval processes.
This paper describes MIRACLE (Multilingual Information RetrievAl for the CLEf campaign) approach and results for the mono, bi and multilingual Cross Language Evaluation Forum tasks. The approach is based on the combination of linguistic and statistic techniques to perform indexing and retrieval tasks.
This paper presents the approaches used by the MIRACLE team to image retrieval at ImageCLEF 2005. Text-based and content-based techniques have been tested, along with combination of both types of methods to improve image retrieval. The text-based experiments defined this year try to use semantic information sources, like thesaurus with semantic data or text(More)
The hypothesis which this paper tries to validate is that text based image retrieval could be improved by the use of semantic information, by means of an expansion algorithm and a module specifically designed to exclude common words and negated words from queries. The expansion algorithm applies specification marks to disambiguate words making use of(More)
We present the miraQA system that constitutes MIRACLE first experience in Question Answering for monolingual Spanish and has been developed for QA@CLEF 2004. The architecture of the system is described and details of our approach to Statistical Answer Extraction based on Hidden Markov Models are presented. One run that uses last year question set for(More)
This paper presents a text summarization system for the Spanish language that combines classic techniques in automatic summarization with less frequent ones, like anaphora resolution and cohesive markers detection in order to fight the lack of coherence intrinsic to automatic text excerpts.
This paper presents the 2005 MIRACLE's team approach to CLEF QA with Spanish as a target task using miraQA system. The system is based on answer extraction and uses mainly syntactic patterns and semantic information. Six runs were submitted for Spanish, English and Italian as source languages using commercial translation software. The system performs(More)