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Ad hoc retrieval with Marathi language
Auteur(s)
Akasereh, Mitra
In
Multilingual Information Access in South Asian Languages, Springer, 2013///23-37
Résumé
Our goal in participating in FIRE 2011 evaluation campaign is to analyse and evaluate the retrieval effectiveness of our implemented retrieval system when using Marathi language. We have developed a light and an aggressive stemmer for this language as well as a stopword list. In our experiment seven different IR models (language model, DFR-PL2, DFR-PB2, DFR-GL2, DFR-I(<i>n <sub>e</sub></i>)C2, <i>tf idf</i> and Okapi) were used to evaluate the influence of these stemmers as well as <i>n</i>-grams and trunc-<i>n</i> language-independent indexing strategies, on retrieval performance. We also applied a pseudo relevance-feedback or blind-query expansion approach to estimate the impact of this approach on enhancing the retrieval effectiveness. Our results show that for Marathi language DFR-I(<i>n <sub>e</sub></i>)C2, DFR-PL2 and Okapi IR models result the best performance. For this language trunc-<i>n</i> indexing strategy gives the best retrieval effectiveness comparing to other stemming and indexing approaches. Also the adopted pseudo-relevance feedback approach tends to enhance the retrieval effectiveness.
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Type de publication
journal article
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