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This paper presents an approach of a cross-lingual information retrieval which uses a ranking method based on a penalisation version of the Jaccard formula. The obtained results after the submission of a set of runs to the WebCLEF 2006 have shown that this simple ranking formula may be used in a cross-lingual environment. A comparison with runs submitted by other teams ranks us in a third place by using all the topics. A fourth place is obtained with our best overall results by using only the new topic set, and a second place was got by using only the automatic topics of the new topic set. An exact comparison with the rest of the participants is in fact difficult to obtain and, therefore, we consider that further detailed analysis of the components should be done in order to determine the best components of the proposed system.

This paper presents an approach of a cross-lingual information retrieval which uses a ranking method based on a penalisation version of the Jaccard formula. The obtained results after the submission of a set of runs to the WebCLEF 2006 have shown that this simple ranking formula may be used in a cross-lingual environment. A comparison with runs submitted by other teams ranks us in a third place by using all the topics. A fourth place is obtained with our best overall results by using only the new topic set, and a second place was got by using only the automatic topics of the new topic set. An exact comparison with the rest of the participants is in fact difficult to obtain and, therefore, we consider that further detailed analysis of the components should be done in order to determine the best components of the proposed system.

This paper presents an approach of a cross-lingual information retrieval which uses a ranking method based on a penalisation version of the Jaccard formula. The obtained results after the submission of a set of runs to the WebCLEF 2006 have shown that this simple ranking formula may be used in a cross-lingual environment. A comparison with runs submitted by other teams ranks us in a third place by using all the topics. A fourth place is obtained with our best overall results by using only the new topic set, and a second place was got by using only the automatic topics of the new topic set. An exact comparison with the rest of the participants is in fact difficult to obtain and, therefore, we consider that further detailed analysis of the components should be done in order to determine the best components of the proposed system.

This paper presents an approach of a cross-lingual information retrieval which uses a ranking method based on a penalisation version of the Jaccard formula. The obtained results after the submission of a set of runs to the WebCLEF 2006 have shown that this simple ranking formula may be used in a cross-lingual environment. A comparison with runs submitted by other teams ranks us in a third place by using all the topics. A fourth place is obtained with our best overall results by using only the new topic set, and a second place was got by using only the automatic topics of the new topic set. An exact comparison with the rest of the participants is in fact difficult to obtain and, therefore, we consider that further detailed analysis of the components should be done in order to determine the best components of the proposed system.

This paper presents an approach of a cross-lingual information retrieval which uses a ranking method based on a penalisation version of the Jaccard formula. The obtained results after the submission of a set of runs to the WebCLEF 2006 have shown that this simple ranking formula may be used in a cross-lingual environment. A comparison with runs submitted by other teams ranks us in a third place by using all the topics. A fourth place is obtained with our best overall results by using only the new topic set, and a second place was got by using only the automatic topics of the new topic set. An exact comparison with the rest of the participants is in fact difficult to obtain and, therefore, we consider that further detailed analysis of the components should be done in order to determine the best components of the proposed system.

This paper presents an approach of a cross-lingual information retrieval which uses a ranking method based on a penalisation version of the Jaccard formula. The obtained results after the submission of a set of runs to the WebCLEF 2006 have shown that this simple ranking formula may be used in a cross-lingual environment. A comparison with runs submitted by other teams ranks us in a third place by using all the topics. A fourth place is obtained with our best overall results by using only the new topic set, and a second place was got by using only the automatic topics of the new topic set. An exact comparison with the rest of the participants is in fact difficult to obtain and, therefore, we consider that further detailed analysis of the components should be done in order to determine the best components of the proposed system.