About: Similarity Search: The Metric Space Approach     Goto   Sponge   Distinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • Similarity searching has become afundamental computational task in a variety of application areas, including multimedia information retrieval, data mining, pattern recognition, machine learning, computer vision, biomedical databases, data compression and statistical data analysis. In such environments, an exact match has little meaning, and proximity/distance (similarity/dissimilarity) concepts are typically much more fruitful for searching. In this tutorial, we review the state of the art in developing similarity search mechanisms that accept the metric space paradigm. We explain the high extensibility of the metric space approach and demonstrate its capability with examples of distance functions. The efforts to further speed up retrieval are demonstrated by a class of approximated techniques and the very recent proposals of scalable and distributed structures based on the P2P communication paradigm.
  • Similarity searching has become afundamental computational task in a variety of application areas, including multimedia information retrieval, data mining, pattern recognition, machine learning, computer vision, biomedical databases, data compression and statistical data analysis. In such environments, an exact match has little meaning, and proximity/distance (similarity/dissimilarity) concepts are typically much more fruitful for searching. In this tutorial, we review the state of the art in developing similarity search mechanisms that accept the metric space paradigm. We explain the high extensibility of the metric space approach and demonstrate its capability with examples of distance functions. The efforts to further speed up retrieval are demonstrated by a class of approximated techniques and the very recent proposals of scalable and distributed structures based on the P2P communication paradigm. (en)
  • Similarity searching has become afundamental computational task in a variety of application areas, including multimedia information retrieval, data mining, pattern recognition, machine learning, computer vision, biomedical databases, data compression and statistical data analysis. In such environments, an exact match has little meaning, and proximity/distance (similarity/dissimilarity) concepts are typically much more fruitful for searching. In this tutorial, we review the state of the art in developing similarity search mechanisms that accept the metric space paradigm. We explain the high extensibility of the metric space approach and demonstrate its capability with examples of distance functions. The efforts to further speed up retrieval are demonstrated by a class of approximated techniques and the very recent proposals of scalable and distributed structures based on the P2P communication paradigm. (cs)
Title
  • Similarity Search: The Metric Space Approach
  • Similarity Search: The Metric Space Approach (en)
  • Podobnostní hledání: Pohled metrického prostoru (cs)
skos:prefLabel
  • Similarity Search: The Metric Space Approach
  • Similarity Search: The Metric Space Approach (en)
  • Podobnostní hledání: Pohled metrického prostoru (cs)
skos:notation
  • RIV/00216224:14330/07:00019397!RIV08-AV0-14330___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1ET100300419), P(GP201/07/P240)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 449808
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/07:00019397
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • similarity search; approximate search; metric space; index structures; distributed index structure; scalability (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...i/riv/kodPristupu
http://linked.open...ontrolniKodProRIV
  • [3517398EF4EE]
http://linked.open...i/riv/mistoVydani
  • Seoul, Korea
http://linked.open...n/vavai/riv/nosic
  • N/A
http://linked.open...telVyzkumneZpravy
  • ACM
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Zezula, Pavel
  • Dohnal, Vlastislav
  • Amato, Giuseppe
http://linked.open...rzeVyzkumneZpravy
  • ACM SAC 2007 Conference
http://localhost/t...ganizacniJednotka
  • 14330
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 84 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software