Abstract
Searching for similar objects in a dataset, with respect to a query object and a distance, is a fundamental problem for several applications that use complex data. The main difficulties is to focus the search on as few elements as possible and to further limit the computationally-extensive distance calculations between them. Here, we introduce a forest data structure for indexing and querying such data. The efficiency of our proposal is studied through experiments on real-world datasets and a comparison with previous proposals.
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Martinez, J., Kouahla, Z. (2012). Indexing Metric Spaces with Nested Forests. In: Liddle, S.W., Schewe, KD., Tjoa, A.M., Zhou, X. (eds) Database and Expert Systems Applications. DEXA 2012. Lecture Notes in Computer Science, vol 7447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32597-7_41
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DOI: https://doi.org/10.1007/978-3-642-32597-7_41
Publisher Name: Springer, Berlin, Heidelberg
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