Dimensionality reduction for dimension-specific search.
(2007)
Presentation / Conference
HUANG, Z., SHEN, H., ZHOU, X., SONG, D. and RUGER, S. 2007. Dimensionality reduction for dimension-specific search. In Proceedings of the 30th Annual international Association of Computing Machinery Special Interest Group on Information Retrieval (ACM SIGIR) conference on research and development in information retrieval (SIGIR'07), 23-27 July 2007, Amsterdam, Netherlands. New York: ACM [online], pages 849-850. Available from: https://doi.org/10.1145/1277741.1277940
Dimensionality reduction plays an important role in efficient similarity search, which is often based on k-nearest neighbor (k-NN) queries over a high-dimensional feature space. In this paper, we introduce a novel type of k-NN query, namely condition... Read More about Dimensionality reduction for dimension-specific search..