Abstract
The Distance Index (D-index) is a recently introduced metric indexing structure which capable of state-of-the-art performance in large scale metric search applications. In this paper we address the problem of how to balance the D-index structure for more efficient similarity search. A group of evaluation functions measuring the balance property of a D-index structure are introduced to guide the construction of the indexing structure. The optimization is formulated in a genetic representation that is effectively solved by a generic genetic algorithm (GA). Compared with the classic D-index, balanced D-index structures show a significant improvement in reduction of distance calculations while maintaining a good input-output (IO) performance.
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Ban, T. (2008). Using Genetic Algorithm to Balance the D-Index Algorithm for Metric Search. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds) Neural Information Processing. ICONIP 2007. Lecture Notes in Computer Science, vol 4985. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69162-4_28
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DOI: https://doi.org/10.1007/978-3-540-69162-4_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69159-4
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