Pattern-preserving k-anonymization of sequences and its application to mobility data mining (Contributo in atti di convegno)

Type

• Contributo in atti di convegno (Classe)
• Prodotto della ricerca (Classe)

Label

• Pattern-preserving k-anonymization of sequences and its application to mobility data mining (Contributo in atti di convegno) (literal)

Anno

• 2008-01-01T00:00:00+01:00 (literal)

Alternative label

• Pensa R. G.; Monreale A.; Pinelli F.; Pedreschi D. (2008)
  Pattern-preserving k-anonymization of sequences and its application to mobility data mining
  in The 1st International Workshop on Privacy in Location-Based Applications, Malaga, Spain
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Pensa R. G.; Monreale A.; Pinelli F.; Pedreschi D. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note

• In: PiLBA 2008 - The 1st International Workshop on Privacy in Location-Based Applications (Malaga, Spain, 9 ottobre 2008). Proceedings, vol. 397 pp. 44 - 60. CEUR-WS.org, 2008. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto

• ABSTRACT: Sequential pattern mining is a major research field in knowledge discovery and data mining. Thanks to the increasing availability of transaction data, it is now possible to provide new and improved services based on users' and customers' behavior. However, this puts the citizen's privacy at risk. Thus, it is important to develop new privacy-preserving data mining techniques that do not alter the analysis results significantly. In this paper we propose a new approach for anonymizing sequential data by hiding infrequent, and thus potentially sensible, subsequences. Our approach guarantees that the disclosed data are k-anonymous and preserve the quality of extracted patterns. An application to a real-world moving object database is presented, which shows the effectiveness of our approach also in complex contexts. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• CNR-ISTI, Pisa, Università di Pisa (literal)

Titolo

• Pattern-preserving k-anonymization of sequences and its application to mobility data mining (literal)

Prodotto di

• Knowledge Discovery and Data Mining (ICT.P08.009.003) (Modulo)
• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)

Autore CNR

• DINO PEDRESCHI (Persona)
• FABIO PINELLI (Unità di personale esterno)
• Anna Monreale (Persona)
• RUGGERO GAETANO PENSA (Persona)

Insieme di parole chiave

• Parole chiave di "Pattern-preserving k-anonymization of sequences and its application to mobility data mining" (Insieme di parole chiave)

Incoming links:

Prodotto

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Knowledge Discovery and Data Mining (ICT.P08.009.003) (Modulo)

Autore CNR di

• FABIO PINELLI (Unità di personale esterno)
• Anna Monreale (Persona)
• RUGGERO GAETANO PENSA (Persona)
• DINO PEDRESCHI (Persona)

Insieme di parole chiave di

• Parole chiave di "Pattern-preserving k-anonymization of sequences and its application to mobility data mining" (Insieme di parole chiave)