Towards Efficient Indexing of Arbitrary Similarity

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@Article{Bartos:2013:SIGMOD,
  author =       "Tomas Bartos and Tomas Skopal and Juraj Mosko",
  title =        "Towards Efficient Indexing of Arbitrary Similarity",
  journal =      "SIGMOD Record",
  year =         "2013",
  volume =       "42",
  number =       "2",
  pages =        "5--10",
  month =        jul,
  note =         "Vision Paper. ACM Special Interest Group on Management
                 of Data",
  keywords =     "genetic algorithms, genetic programming",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/sigmod.bib",
  acmid =        "2503794",
  publisher =    "ACM",
  address =      "New York, NY, USA",
  ISSN =         "0163-5808",
  URL =          "http://doi.acm.org/10.1145/2503792.2503794",
  DOI =          "doi:10.1145/2503792.2503794",
  size =         "6 pages",
  abstract =     "The popularity of similarity search expanded with the
                 increased interest in multimedia databases,
                 bioinformatics, or social networks, and with the
                 growing number of users trying to find information in
                 huge collections of unstructured data. During the
                 exploration, the users handle database objects in
                 different ways based on the used similarity models,
                 ranging from simple to complex models. Efficient
                 indexing techniques for similarity search are required
                 especially for growing databases. In this paper, we
                 study implementation possibilities of the recently
                 announced theoretical framework SIMDEX, the task of
                 which is to algorithmically explore a given similarity
                 space and find possibilities for efficient indexing.
                 Instead of a fixed set of indexing properties, such as
                 metric space axioms, SIMDEX aims to seek for
                 alternative properties that are valid in a particular
                 similarity model (database) and, at the same time,
                 provide efficient indexing. In particular, we propose
                 to implement the fundamental parts of SIMDEX by means
                 of the genetic programming (GP) which we expect will
                 provide high-quality resulting set of expressions
                 (axioms) useful for indexing.",
  acknowledgement = "Nelson H. F. Beebe, University of Utah, Department
                 of Mathematics, 110 LCB, 155 S 1400 E RM 233, Salt Lake
                 City, UT 84112-0090, USA, Tel: +1 801 581 5254, FAX: +1
                 801 581 4148, e-mail: \path|beebe@math.utah.edu|,
                 \path|beebe@acm.org|, \path|beebe@computer.org|
                 (Internet), URL:
                 \path|http://www.math.utah.edu/~beebe/|",
  notes =        "Bartos:2013:TEI:2503792.2503794",
}

Genetic Programming entries for Tomas Bartos Tomas Skopal Juraj Mosko

Citations