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[TMF09] A Comparative Study of Diversity Methods for Hybrid Text and Image Retrieval Approaches
Conférence Internationale avec comité de lecture : Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access (CLEF'08), October 2009, pp.585-592, Series LNCS,Mots clés: Image Databases, Relevance Feedback, Statistical Learning, Image Retrieval, Multimodal text and Image Retrieval
Résumé:
This article compares eight different diversity methods: 3
based on visual information, 1 based on date information, 3 adapted to
each topic based on location and visual information; finally, for completeness,
1 based on random permutation. To compare the effectiveness
of these methods, we apply them on 26 runs obtained with varied methods
from different research teams and based on different modalities. We
then discuss the results of the more than 200 obtained runs. The results
show that query-adapted methods are more efficient than non-adapted
method, that visual only runs are more difficult to diversify than text
only and text-image runs, and finally that only few methods maximize
both the precision and the cluster recall at 20 documents.
Equipe:
vertigo
BibTeX
| @inproceedings { | |||
| TMF09, | |||
| title | = | "{A Comparative Study of Diversity Methods for Hybrid Text and Image Retrieval Approaches}", | |
| author | = | " S. Tollari and P. Mulhem and M. Ferecatu and H. Glotin and M. Detyniecki and P. Gallinari and H. Sahbi and Z. Zhao ", | |
| booktitle | = | "{Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access (CLEF'08)}", | |
| year | = | 2009, | |
| month | = | "October", | |
| series | = | "LNCS", | |
| pages | = | "585-592", | |
| } | |||
