Automatic discovery of query-class-dependent models for multimodal search
Proceedings of the 13th annual ACM international conference on Multimedia
Probabilistic latent query analysis for combining multiple retrieval sources
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
CompositeMap: a novel framework for music similarity measure
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
MM '09 Proceedings of the 17th ACM international conference on Multimedia
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In this paper, we propose a novel multimodal fusion framework, document dependent fusion (DDF), which derives the optimal combination strategy for each individual document in the fusion process. For each document, we derive a document weight vector by estimating the descriptive abilities of its different modalities. The document weight vector also enables our framework to be easily integrated with existing multimodal fusion schemes, and achieve a better combination strategy for each document given a query. Experiments are conducted on a 17174-song music database to compare the retrieval accuracy of traditional query independent fusion and query dependent fusion approaches, and that obtained after integrating DDF with them. Experimental results indicate that DDF can significantly improve the retrieval performance of current fusion approaches.