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Experiments are conducted to evaluate the performance of the methods. The results show that the methods can effectively preserve privacy without losing much classification accuracy and within a specified limit of aggregation error.<\/p>","DOI":"10.4018\/jdwm.2011100104","type":"journal-article","created":{"date-parts":[[2011,10,19]],"date-time":"2011-10-19T12:11:46Z","timestamp":1319026306000},"page":"64-85","source":"Crossref","is-referenced-by-count":2,"title":["Preserving Privacy in Time Series Data Mining"],"prefix":"10.4018","volume":"7","author":[{"given":"Ye","family":"Zhu","sequence":"first","affiliation":[{"name":"Cleveland State University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongjian","family":"Fu","sequence":"additional","affiliation":[{"name":"Cleveland State University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huirong","family":"Fu","sequence":"additional","affiliation":[{"name":"Oakland University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jdwm.2011100104-0","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Faloutsos, C., & Swami, A. 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