"M-Index; Signature Quadratic Form Distance; Content-based Retrieval; Approximate Search; Similarity Search"@en . . . "P(GAP202/11/0968), P(GPP202/12/P297)" . "6th International Conference, SISAP 2013" . "11320" . "93793" . "7"^^ . . "10.1007/978-3-642-41062-8_31" . . "RIV/00216208:11320/13:10192541!RIV14-GA0-11320___" . "Skopal, Tom\u00E1\u0161" . "On Scalable Approximate Search with the Signature Quadratic Form Distance"@en . "3"^^ . . "On Scalable Approximate Search with the Signature Quadratic Form Distance" . "The signature quadratic form distance and feature signatures have become a respected similarity space for effective content-based retrieval. Furthermore, the similarity space is configurable by a parameter alpha affecting both retrieval precision and intrinsic dimensionality, and thus interesting trade-offs can be achieved when a metric index is used for exact search. In this paper we combine such configurable model with state of the art approximate search techniques developed for the M-Index. In the experiments, we show that employing a configuration resulting in the best effectiveness of the measure leads also to very competitive approximate search effectiveness when using the M-Index, regardless the high intrinsic dimensionality of the corresponding similarity space." . . "3"^^ . . "Berlin Heidelberg Germany" . "Springer-Verlag" . . . . "On Scalable Approximate Search with the Signature Quadratic Form Distance" . . "The signature quadratic form distance and feature signatures have become a respected similarity space for effective content-based retrieval. Furthermore, the similarity space is configurable by a parameter alpha affecting both retrieval precision and intrinsic dimensionality, and thus interesting trade-offs can be achieved when a metric index is used for exact search. In this paper we combine such configurable model with state of the art approximate search techniques developed for the M-Index. In the experiments, we show that employing a configuration resulting in the best effectiveness of the measure leads also to very competitive approximate search effectiveness when using the M-Index, regardless the high intrinsic dimensionality of the corresponding similarity space."@en . "2013-10-02+02:00"^^ . "Gro\u0161up, Tom\u00E1\u0161" . . "978-3-642-41062-8" . . . . "Loko\u010D, Jakub" . . . . "0302-9743" . "RIV/00216208:11320/13:10192541" . . "La Coruna, Spain" . . . "[B7EC4BD12693]" . "On Scalable Approximate Search with the Signature Quadratic Form Distance"@en . .