SYNONYMS
Indexing for similarity search
DEFINITION
The term High Dimensional Indexing [6,9] subsumes all techniques for indexing vector spaces addressing problems which are specific in the context of high dimensional data spaces, and all optimization techniques to improve index structures, and the algorithms for various variants of similarity search (nearest neighbor, reverse nearest neighbor queries, range queries, similarity joins etc.) for high dimensional spaces. The well-known Curse of Dimensionality leads to a worsening of the index selectivity with increasing dimensionality of the data space, an effect which already starts at dimensions of 10–15, also depending on the size of the database and the data distribution (clustering, attribute dependencies). During query processing, large parts of conventional hierarchical indexes (e.g., R-tree) need to be randomly accessed, which is by a factor of up to 20 more expensive than sequential reading operations. Therefore, specialized...
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Böhm, C., Plant, C. (2009). High Dimensional Indexing. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_804
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DOI: https://doi.org/10.1007/978-0-387-39940-9_804
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