Lyndon Kennedy, Paul Natsev, Shih-Fu Chang. Automatic Discovery of Query Class Dependent Models for Multimodal Search. In ACM Multimedia, Singapore, November 2005.
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We develop a framework for the automatic discovery of query classes for queryclassdependent search models in multimodal retrieval. The framework automatically discovers useful query classes by clustering queries in a training set according to the performance of various unimodal search methods, yielding classes of queries which have similar fusion strategies for the combination of unimodal components for multimodal search. We further combine these performance features with the semantic features of the queries during clustering in order to make discovered classes meaningful. The inclusion of the semantic space also makes it possible to choose the correct class for new, unseen queries, which have unknown performance space features. We evaluate the system against the TRECVID 2004 automatic video search task and find that the automatically discovered query classes give an improvement of 18% in MAP over handdefined query classes used in previous works. We also find that some handdefined query classes, such as Named Person and Sports do, indeed, have similarities in search method performance and are useful for queryclassdependent multimodal search, while other handdefined classes, such as Named Object and General Object do not have consistent search method performance and should be split apart or replaced with other classes. The proposed framework is general and can be applied to any new domain without expert domain knowledge.
@InProceedings{kennedy:acmmm05,
Author = {Kennedy, Lyndon and Natsev, Paul and Chang, Shih-Fu},
Title = {Automatic Discovery of Query Class Dependent Models for Multimodal Search},
BookTitle = {ACM Multimedia},
Address = {Singapore},
Month = {November},
Year = {2005}
}
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