JHU/APL Ad Hoc Experiments at CLEF 2006
Identifieur interne : 001C05 ( Main/Exploration ); précédent : 001C04; suivant : 001C06JHU/APL Ad Hoc Experiments at CLEF 2006
Auteurs : Paul Mcnamee [États-Unis]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: JHU/APL continued its participation in multilingual retrieval at CLEF in 2006. We again applied our hallmark technique for combating language diversity and morphological complexity: character n-gram tokenization. This year we participated in the ad hoc cross-language track and submitted both monolingual and bilingual runs. Our experimental results this year agree with our previous reports that n-grams perform especially well in linguistically complex languages, notably Bulgarian and Hungarian, where monolingual improvements of 27% and 70% respectively were observed compared to space-delimited word forms. As in CLEF 2005, our bilingual submissions made use of subword translation, statistical translation of character n-grams using aligned corpora, when parallel data were available, and web-based machine translation, when no suitable data was available to us.
Url:
DOI: 10.1007/978-3-540-74999-8_22
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">Abstract: JHU/APL continued its participation in multilingual retrieval at CLEF in 2006. We again applied our hallmark technique for combating language diversity and morphological complexity: character n-gram tokenization. This year we participated in the ad hoc cross-language track and submitted both monolingual and bilingual runs. Our experimental results this year agree with our previous reports that n-grams perform especially well in linguistically complex languages, notably Bulgarian and Hungarian, where monolingual improvements of 27% and 70% respectively were observed compared to space-delimited word forms. As in CLEF 2005, our bilingual submissions made use of subword translation, statistical translation of character n-grams using aligned corpora, when parallel data were available, and web-based machine translation, when no suitable data was available to us.</div>
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