Publikation:

Probabilistic Proximity Search Algorithms Based on Compact Partitions

Lade...
Vorschaubild

Dateien

BN04Bustos.pdf
BN04Bustos.pdfGröße: 363.25 KBDownloads: 409

Datum

2004

Autor:innen

Bustos Cárdenas, Benjamin Eugenio
Navarro, Gonzalo

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

ArXiv-ID

Internationale Patentnummer

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen in

Journal of discrete algorithms. 2004, 2(1), pp. 115-134. Available under: doi: 10.1016/S1570-8667(03)00067-4

Zusammenfassung

The main bottleneck of the research in metric space searching is the so-called curse of dimensionality, which makes the task of searching some metric spaces intrinsically difficult, whatever algorithm is used. A recent trend to break this bottleneck resorts to probabilistic algorithms, where it has been shown that one can find 99% of the relevant objects at a fraction of the cost of the exact algorithm. These algorithms are welcome in most applications because resorting to metric space searching already involves a fuzziness in the retrieval requirements. In this paper, we push further in this direction by developing probabilistic algorithms on data structures whose exact versions are the best for high dimensions. As a result, we obtain probabilistic algorithms that are better than the previous ones. We give new insights on the problem and propose a novel view based on time-bounded searching. We also propose an experimental framework for probabilistic algorithms that permits comparing them in offline mode.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Metric spaces, Range queries, Probabilistic algorithms, Approximate algorithms, Similarity searching

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690BUSTOS CÁRDENAS, Benjamin Eugenio, Gonzalo NAVARRO, 2004. Probabilistic Proximity Search Algorithms Based on Compact Partitions. In: Journal of discrete algorithms. 2004, 2(1), pp. 115-134. Available under: doi: 10.1016/S1570-8667(03)00067-4
BibTex
@article{BustosCardenas2004Proba-5539,
  year={2004},
  doi={10.1016/S1570-8667(03)00067-4},
  title={Probabilistic Proximity Search Algorithms Based on Compact Partitions},
  number={1},
  volume={2},
  journal={Journal of discrete algorithms},
  pages={115--134},
  author={Bustos Cárdenas, Benjamin Eugenio and Navarro, Gonzalo}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/5539">
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5539"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:56:18Z</dcterms:available>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:bibliographicCitation>First publ. in: Journal of discrete algorithms 2 (2004), 1, pp. 115-134</dcterms:bibliographicCitation>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Navarro, Gonzalo</dc:creator>
    <dcterms:abstract xml:lang="eng">The main bottleneck of the research in metric space searching is the so-called curse of dimensionality, which makes the task of searching some metric spaces intrinsically difficult, whatever algorithm is used. A recent trend to break this bottleneck resorts to probabilistic algorithms, where it has been shown that one can find 99% of the relevant objects at a fraction of the cost of the exact algorithm. These algorithms are welcome in most applications because resorting to metric space searching already involves a fuzziness in the retrieval requirements. In this paper, we push further in this direction by developing probabilistic algorithms on data structures whose exact versions are the best for high dimensions. As a result, we obtain probabilistic algorithms that are better than the previous ones. We give new insights on the problem and propose a novel view based on time-bounded searching. We also propose an experimental framework for probabilistic algorithms that permits comparing them in offline mode.</dcterms:abstract>
    <dc:rights>Attribution-NonCommercial-NoDerivs 2.0 Generic</dc:rights>
    <dcterms:issued>2004</dcterms:issued>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:56:18Z</dc:date>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5539/1/BN04Bustos.pdf"/>
    <dc:creator>Bustos Cárdenas, Benjamin Eugenio</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Bustos Cárdenas, Benjamin Eugenio</dc:contributor>
    <dc:language>eng</dc:language>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by-nc-nd/2.0/"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5539/1/BN04Bustos.pdf"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:title>Probabilistic Proximity Search Algorithms Based on Compact Partitions</dcterms:title>
    <dc:contributor>Navarro, Gonzalo</dc:contributor>
    <dc:format>application/pdf</dc:format>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Begutachtet
Diese Publikation teilen