Abstract
High-dimensional indexes do not work because of the often-cited “curse of dimensionality.” However, users are usually interested in querying data over a relatively small subset of the entire attribute set at a time. A potential solution is to use lower dimensional indexes that accurately represent the user access patterns. To address these issues, in this paper we propose a parameterizable technique to recommend indexes based on index types.
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Rajesh, S., Jilla, K., Rajiv, K., Prasad, T.V.K.P. (2014). Effect of Indexing on High-Dimensional Databases Using Query Workloads. In: Satapathy, S., Avadhani, P., Udgata, S., Lakshminarayana, S. (eds) ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol II. Advances in Intelligent Systems and Computing, vol 249. Springer, Cham. https://doi.org/10.1007/978-3-319-03095-1_72
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DOI: https://doi.org/10.1007/978-3-319-03095-1_72
Publisher Name: Springer, Cham
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