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One of the most known frameworks of data anonymization is\n                    <jats:italic>k<\/jats:italic>\n                    -anonymity, this method assumes that a dataset is anonymous if and only if for each element of the dataset, there exist at least\n                    <jats:italic>k<\/jats:italic>\n                    \u2212 1 elements identical to it. In this paper, we propose two techniques to achieve\n                    <jats:italic>k<\/jats:italic>\n                    -anonymity through microaggregation:\n                    <jats:italic>k<\/jats:italic>\n                    -CMVM and Constrained-CMVM. Both, use topological collaborative clustering to obtain\n                    <jats:italic>k<\/jats:italic>\n                    -anonymous data. The first one determines the\n                    <jats:italic>k<\/jats:italic>\n                    levels automatically and the second defines it by exploration. We also improved the results of these two approaches by using pLVQ2 as a weighted vector quantization method. The four methods proposed were proven to be efficient using two data utility measures, the separability utility and the structural utility. The experimental results have shown a very promising performance.\n                  <\/jats:p>","DOI":"10.1515\/jisys-2020-0026","type":"journal-article","created":{"date-parts":[[2020,10,5]],"date-time":"2020-10-05T15:47:46Z","timestamp":1601912866000},"page":"327-345","source":"Crossref","is-referenced-by-count":1,"title":["Data Anonymization through Collaborative Multi-view Microaggregation"],"prefix":"10.1515","volume":"30","author":[{"given":"Sarah","family":"Zouinina","sequence":"first","affiliation":[{"name":"Universit\u00e9 Sorbonne Paris Nord, LIPN UMR CNRS , France"},{"name":"Universit\u00e9 Abdelmalek Essaadi, ENSA of Tangier , LTI , Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Youn\u00e8s","family":"Bennani","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Sorbonne Paris Nord, LIPN UMR CNRS , France"},{"name":"LaMSN, La Maison des Sciences Num\u00e9riques , USPN , France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicoleta","family":"Rogovschi","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Paris , LIPADE , France"},{"name":"LaMSN, La Maison des Sciences Num\u00e9riques , USPN , France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdelouahid","family":"Lyhyaoui","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Abdelmalek Essaadi, ENSA of Tangier , LTI , Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2020,10,2]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Rakesh Agrawal and Ramakrishnan Srikant. 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