Effective Detection of XML Outliers (Contributo in atti di convegno)

Type
Label
  • Effective Detection of XML Outliers (Contributo in atti di convegno) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.3233/978-1-61499-105-2-1221 (literal)
Alternative label
  • Alfredo Cuzzocrea, Giuseppe Manco, Elio Masciari (2012)
    Effective Detection of XML Outliers
    in 16th Annual KES Conference, San Sebastian, 10-12 September 2012
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Alfredo Cuzzocrea, Giuseppe Manco, Elio Masciari (literal)
Pagina inizio
  • 1221 (literal)
Pagina fine
  • 1232 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Advances in Knowledge-Based and Intelligent Information and Engineering Systems - 16th Annual KES Conference (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 243 (literal)
Rivista
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ICAR-CNR (literal)
Titolo
  • Effective Detection of XML Outliers (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-1-61499-104-5 (literal)
Abstract
  • XML (eXtensible Markup Language) became in recent years the new standard for data representation and exchange on the WWW. This has resulted in a great need for data cleaning techniques in order to identify outlying data. In this paper, we present a technique for outlier detection that singles out anomalies with respect to a relevant group of objects. We exploit a suitable encoding of XML documents that are encoded as signals of fixed frequency that can be transformed using Fourier Transforms. Outliers are identified by simply looking at the signal spectra. The results show the effectiveness of our approach. (literal)
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