{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:07:28Z","timestamp":1753880848198,"version":"3.41.2"},"reference-count":31,"publisher":"World Scientific Pub Co Pte Ltd","issue":"Supp02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Inter. Net."],"published-print":{"date-parts":[[2022,4]]},"abstract":"<jats:p> There are various applications of clustering in the fields of machine learning, data mining, data compression along with pattern recognition. The existent techniques like the Llyods algorithm (sometimes called k-means) were affected by the issue of the algorithm which converges to a local optimum along with no approximation guarantee. For overcoming these shortcomings, an efficient k-means clustering approach is offered by this paper for stream data mining. Coreset is a popular and fundamental concept for k-means clustering in stream data. In each step, reduction determines a coreset of inputs, and represents the error, where P represents number of input points according to nested property of coreset. Hence, a bit reduction in error of final coreset gets n times more accurate. Therefore, this motivated the author to propose a new coreset-reduction algorithm. The proposed algorithm executed on the Covertype dataset, Spambase dataset, Census 1990 dataset, Bigcross dataset, and Tower dataset. Our algorithm outperforms with competitive algorithms like Streamkm++, BICO (BIRCH meets Coresets for k-means clustering), and BIRCH (Balance Iterative Reducing and Clustering using Hierarchies. <\/jats:p>","DOI":"10.1142\/s0219265921430118","type":"journal-article","created":{"date-parts":[[2021,12,6]],"date-time":"2021-12-06T02:14:47Z","timestamp":1638756887000},"source":"Crossref","is-referenced-by-count":2,"title":["A Clustering Algorithm in Stream Data Using Strong Coreset"],"prefix":"10.1142","volume":"22","author":[{"given":"Manmohan","family":"Singh","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Dhanbad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rajendra","family":"Pamula","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Dhanbad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alok","family":"Kumar","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Government College of Engineering, Dharmapuri, Tamilnadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2021,12,6]]},"reference":[{"key":"S0219265921430118BIB001","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-016-6902-7"},{"key":"S0219265921430118BIB002","first-page":"439","volume-title":"In Proceedings of the 12th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)","author":"Mishra N.","year":"2001"},{"key":"S0219265921430118BIB003","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2002.994785"},{"key":"S0219265921430118BIB004","first-page":"2","volume":"17","author":"Ackermann M. 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