SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Advances in Informational Retrieval: Recent Research from the Center for Intelligent Information Retrieval
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Relevance Feedback Techniques for Color-based Image Retrieval
MMM '98 Proceedings of the 1998 Conference on MultiMedia Modeling
Local feature extraction and its applications using a library of bases
Local feature extraction and its applications using a library of bases
A pivot-based index structure for combination of feature vectors
Proceedings of the 2005 ACM symposium on Applied computing
Dynamic similarity search in multi-metric spaces
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
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Similarity search in complex databases is of utmost interest in a wide range of application domains. Often, complex objects are described by several representations. The combination of these different representations usually contains more information compared to only one representation. In our work, we introduce the use of an index structure in combination with a negotiation-theory-based approach for deriving a suitable subset of representations for a given query object. This most promising subset of representations is determined in an unsupervised way at query time. We experimentally show how this approach significantly increases the efficiency of the query processing step. At the same time the effectiveness, i.e. the quality of the search results, is equal or even higher compared to standard combination methods.