Antonio Ferrandez

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Antonio Ferrandez is an author.

Publications

Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Exploiting Wikipedia and EuroWordNet to solve Cross-Lingual Question Answering Information Sciences English 2009 This paper describes a new advance in solving Cross-Lingual Question Answering (CL–QA) tasks. It is built on three main pillars: (i) the use of several multilingual knowledge resources to reference words between languages (the Inter Lingual Index (ILI) module of EuroWordNet and the multilingual knowledge encoded in Wikipedia); (ii) the consideration of more than only one translation per word in order to search candidate answers; and (iii) the analysis of the question in the original language without any translation process. This novel approach overcomes the errors caused by the common use of Machine Translation (MT) services by CL–QA systems. We also expose some studies and experiments that justify the importance of analyzing whether a Named Entity should be translated or not. Experimental results in bilingual scenarios show that our approach performs better than an MT based CL–QA approach achieving an average improvement of 36.7%.
This paper describes a new advance in solving {Cross-Lingual} Question Answering {(CL-QA)} tasks. It is built on three main pillars: (i) the use of several multilingual knowledge resources to reference words between languages (the Inter Lingual Index {(ILI)} module of {EuroWordNet} and the multilingual knowledge encoded in Wikipedia); (ii) the consideration of more than only one translation per word in order to search candidate answers; and (iii) the analysis of the question in the original language without any translation process. This novel approach overcomes the errors caused by the common use of Machine Translation {(MT)} services by {CL-QA} systems. We also expose some studies and experiments that justify the importance of analyzing whether a Named Entity should be translated or not. Experimental results in bilingual scenarios show that our approach performs better than an {MT} based {CL-QA} approach achieving an average improvement of 36.7\%. 2009 Elsevier Inc. All rights reserved.
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Using AliQAn in monolingual QA@CLEF 2008 Lecture Notes in Computer Science English 2009 This paper describes the participation of the system AliQAn in the CLEF 2008 Spanish monolingual QA task. This time, the main goals of the current version of AliQAn were to deal with topic-related questions and to decrease the number of inexact answers. We have also explored the use of the Wikipedia corpora, which have posed some new challenges for the QA task. 0 0
Applying Wikipedia's multilingual knowledge to cross-lingual question answering Lecture Notes in Computer Science English 2007 The application of the multilingual knowledge encoded in Wikipedia to an open-domain Cross-Lingual Question Answering system based on the Inter Lingual Index (ILI) module of EuroWordNet is proposed and evaluated. This strategy overcomes the problems due to ILI's low coverage on proper nouns (Named Entities). Moreover, as these are open class words (highly changing), using a community-based up-to-date resource avoids the tedious maintenance of hand-coded bilingual dictionaries. A study reveals the importance to translate Named Entities in CL-QA and the advantages of relying on Wikipedia over ILI for doing this. Tests on questions from the Cross-Language Evaluation Forum (CLEF) justify our approach (20% of these are correctly answered thanks to Wikipedia's Multilingual Knowledge). 0 0
Applying Wikipedia’s Multilingual Knowledge to Cross-Lingual Question Answering Lecture Notes in Computer Science 2007 The application of the multilingual knowledge encoded in Wikipedia to an open-domain Cross-Lingual Question Answering system based on the Inter Lingual Index (ILI) module of EuroWordNet is proposed and evaluated. This strategy overcomes the problems due to ILI’s low coverage on proper nouns (Named Entities). Moreover, as these are open class words (highly changing), using a community-based up-to-date resource avoids the tedious maintenance of hand-coded bilingual dictionaries. A study reveals the importance to translate Named Entities in CL?QA and the advantages of relying on Wikipedia over ILI for doing this. Tests on questions from the Cross-Language Evaluation Forum (CLEF) justify our approach (20% of these are correctly answered thanks to Wikipedia’s Multilingual Knowledge). 0 0