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Showing results for Pattern-Preserving k-Anonymization of Sequences and its Application to Mobility Data Mining.
Sequential pattern mining is a major research field in knowl- edge discovery and data mining. Thanks to the increasing availability of transaction data, it is ...
Sequential pattern mining is a major research fleld in knowl- edge discovery and data mining. Thanks to the increasing availability of transaction data, ...
A new approach for anonymizing sequential data by hiding infrequent, and thus potentially sensible, subsequences is proposed, which guarantees that the ...
Pattern-Preserving k-Anonymization of Sequences and its Application to Mobility Data Mining, in: PiLBA '08 Privacy in Location-Based Applications, CEUR-WS.org, ...
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 ...
We propose a novel anonymization model called (k,P)-anonymity for pattern-rich time- series. This model publishes both the attribute values and the patterns of ...
Pattern-Preserving k-Anonymization of sequences and its Application to Mobility Data Mining. An Image/Link below is provided (as is) to download presentation ...
92, 2020. Pattern-preserving k-anonymization of sequences and its application to mobility data mining. RG Pensa, A Monreale, F Pinelli, D Pedreschi. CEUR ...
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Monreale, F. Pinelli, and D. Pedreschi. Pattern-preserving k-anonymization of sequences and its application to mobility data mining. In PiLBA, 2008.
Pattern-preserving k-anonymization of sequences and its application to mobility data mining. RG Pensa, A Monreale, F Pinelli, D Pedreschi. CEUR Workshop ...