Rights accessRestricted access - publisher's policy
Nowadays, the management of sequential and temporal data is an increasing need in many data mining processes. Therefore, the development of new privacy preserving data
mining techniques for sequential data is a crucial need to ensure that sequence data analysis is performed without disclosure
sensitive information. Although data analysis and protection are very different processes, they share a few common components such as similarity measurement.
In this paper we propose a new similarity function for categorical sequences of events based on OWA operators and fuzzy quantifiers. The main advantage of this new similarity function is the possibility of incorporating the user preferences in the similarity computation. We describe the implications of the application of different user preference policies in the similarity measurement when microaggregation, a wellknown data protection method, is applied to sequential data.
CitationValls, A.; Nin, J.; Torra, V. On the use of aggregation operators for location privacy. A: Conference of the European Society of Fuzzy Logic and Technology. "2009 European Society of Fuzzy Logic and Technology Conference". Lisbon: 2009, p. 489-494.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder. If you wish to make any use of the work not provided for in the law, please contact: email@example.com