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Over the years, a common approach to outlier detection is using clustering\u2010based methods, but these methods have inherent challenges and drawbacks. These include to effectively cluster sparse data points which has to do with the quality of clustering methods, dealing with continuous fast\u2010incoming data streams, high memory and time consumption, and lack of high outlier detection accuracy. This paper aims at proposing an effective clustering\u2010based approach to detect outliers in evolving data streams. We propose a new method called Effective Microcluster and Minimal pruning CLustering\u2010based method for Outlier detection in Data Streams (EMM\u2010CLODS). It is a clustering\u2010based outlier detection approach that detects outliers in evolving data streams by first applying microclustering technique to cluster dense data points and effectively handle objects within a sliding window according to the relevance of their status to their respective neighbors or position. The analysis from our experimental studies on both synthetic and real\u2010world datasets shows that the technique performs well with minimal memory and time consumption when compared to the other baseline algorithms, making it a very promising technique in dealing with outlier detection problems in data streams.<\/jats:p>","DOI":"10.1155\/2021\/9178461","type":"journal-article","created":{"date-parts":[[2021,9,13]],"date-time":"2021-09-13T19:50:54Z","timestamp":1631562654000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["EMM\u2010CLODS: An Effective Microcluster and Minimal Pruning CLustering\u2010Based Technique for Detecting Outliers in Data Streams"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7335-602X","authenticated-orcid":false,"given":"Mohamed Jaward","family":"Bah","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7521-2871","authenticated-orcid":false,"given":"Hongzhi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3861-1352","authenticated-orcid":false,"given":"Li-Hui","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7167-6970","authenticated-orcid":false,"given":"Ji","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,9,13]]},"reference":[{"key":"e_1_2_11_1_2","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"e_1_2_11_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/widm.19"},{"key":"e_1_2_11_3_2","doi-asserted-by":"publisher","DOI":"10.4108\/trans.sis.2013.01-03.e2"},{"key":"e_1_2_11_4_2","doi-asserted-by":"crossref","unstructured":"CaoL. 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