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MKL-tree: an index structure for high-dimensional vector spaces

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Abstract

In this work, a novel hierarchical data structure for high dimensional data indexing is proposed. MKL-tree is based on dimensionality reduction operated by means of the MKL transform, a multi-space generalization of the KL transform. A local dimensionality reduction is performed at each node of the tree, allowing more selective features to be extracted and thus increasing the discriminating power of the index. The mathematical foundation for nodes and leaves representation and for the techniques aimed to manage the structure is detailed. Moreover, the algorithms for bulk loading MKL-tree (i.e., for creating the tree given a large number of objects simultaneously), for updating and splitting nodes after the insertion of new objects and for performing similarity searches are described. Results are reported for the comparison of MKL-tree with other well-known access methods in terms of I/O and CPU costs and precision of the result in the execution of similarity queries.

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Authors and Affiliations

  1. Corso di Laurea in Scienze dell’Informazione, Università di Bologna, via Sacchi 3, 47023, Cesena, Italy

    Annalisa Franco & Alessandra Lumini

  2. DEIS - CSITE-CNR - Università di Bologna, viale Risorgimento 2, 40136, Bologna, Italy

    Dario Maio

Authors
  1. Annalisa Franco
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  2. Alessandra Lumini
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  3. Dario Maio
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Correspondence to Annalisa Franco.

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Franco, A., Lumini, A. & Maio, D. MKL-tree: an index structure for high-dimensional vector spaces. Multimedia Systems 12, 533–550 (2007). https://doi.org/10.1007/s00530-006-0070-9

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