https://m2.mtmt.hu/ hun 2026-04-30 18:39 JournalArticle 35141484 VALIDATED true 0 false 2025-03-19T14:32:47.384+0000 2025-03-19T14:25:06.342+0000 2024-07-22T08:52:32.074+0000 true 10068889 Hubert Nikolett /api/admin/10068889 Admin true 2025-03-19T19:35:42.490+0000 2025-03-19T19:35:42.490+0000 2025-03-19T14:25:06.569+0000 true 10065569 Pécsi Éva /api/admin/10065569 Admin true false false true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle true 1268360 Conference paper in journal true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle /api/subtype/1268360 Konferenciaközlemény SubType 109 true 1268360 true 1 /api/category/1 Category true 1 Wang, Hu Clustering statistical method of high dimensional sparse data based on fuzzy data true true /api/journal/2150487 REVIEWED true false 2150487 true 2150487 true 1742-6588 1742-6596 Journal FOREIGN 2791 1 012060 012060 2024 Developing effective clustering and statistical methods for high-dimensional sparse data presents unique challenges compared to traditional low-dimensional data. To address this, a novel approach is proposed, leveraging fuzzy data principles to enhance the clustering and statistical performance of high-dimensional sparse datasets. The method builds upon the fuzzy C-means clustering algorithm, introducing key modifications for better suitability to high-dimensional sparse data. One crucial enhancement involves tackling the local optimization problem by optimizing the initial clustering center, significantly reducing clustering statistical time. Replacing the original Euclidean distance with cosine distance improves the clustering and statistical performance of high-dimensional sparse data. Experimental results have shown that this method has superior clustering statistical performance when the data dimensions are different. When the data dimension is low, and the blocking ratio is 10%, the clustering statistical effect is optimal. When the data dimension is high, and the blocking ratio is 40%, the clustering statistical effect is optimal. This method has higher hit rates and clustering statistical efficiency at different sparsity levels. true 2024 true true true true false GOLD 2025-03-19 false http://iopscience.iop.org/1742-6596/ 0 0 0 0 0 0 0 0 0 0 0 0 1 1 false false false false 2024-08-21T09:57:19.298+0000 3 26 0 1 0 false Language 10002 /api/language/10002 Angol English true 2 true PersonAuthorship 118396384 /api/authorship/118396384 1 1.0 true false false Wang Hu true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PublicationIdentifier 26853698 /api/publicationidentifier/26853698 PlainSource 6 /api/publicationsource/6 PublicationSourceType 10001 /api/publicationsourcetype/10001 true true true DOI DOI https://doi.org/@@@ true true 6 true 10.1088/1742-6596/2791/1/012060 https://doi.org/10.1088/1742-6596/2791/1/012060 false true PublicationIdentifier 27529540 /api/publicationidentifier/27529540 PlainSource 3 /api/publicationsource/3 PublicationSourceType 10003 /api/publicationsourcetype/10003 false true true Scopus http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-@@@ true true 3 true 85199257327 http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85199257327 false true PublicationIdentifier 26853699 /api/publicationidentifier/26853699 PlainSource 40 /api/publicationsource/40 PublicationSourceType 10006 /api/publicationsourcetype/10006 true true true Egyéb URL Other URL @@@ true true 40 true https://iopscience.iop.org/article/10.1088/1742-6596/2791/1/012060 https://iopscience.iop.org/article/10.1088/1742-6596/2791/1/012060 false true Reference 55909840 /api/reference/55909840 1 false true Reference 55909841 /api/reference/55909841 2 false true Reference 55909842 /api/reference/55909842 3 false true Reference 55909843 /api/reference/55909843 4 false true Reference 55909844 /api/reference/55909844 5 false true Reference 55909845 /api/reference/55909845 6 false true Reference 55909846 /api/reference/55909846 7 false true Reference 55909847 /api/reference/55909847 8 false true Reference 55909848 /api/reference/55909848 9 false true Reference 55909849 /api/reference/55909849 10 false true /api/publication/35141484 <div class="JournalArticle Publication long-list"> <div class="authors"> <img title="Idézőközlemény" style="float: left" src="/frontend/resources/grid/publication-citation-icon.png"> <div class="autype autype0"> <span class="author-name" >Wang Hu </span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;35141484" target="_blank">Clustering statistical method of high dimensional sparse data based on fuzzy data</a></div> <div> <span class="journal-title">JOURNAL OF PHYSICS-CONFERENCE SERIES</span> <span class="journal-issn">(<a target="_blank" href="https://portal.issn.org/resource/ISSN/1742-6588">1742-6588</a> <a target="_blank" href="https://portal.issn.org/resource/ISSN/1742-6596">1742-6596</a>)</span>: <span class="journal-volume">2791</span> <span class="journal-issue">1</span> <span class="page"> Paper 012060. </span> <span class="year">(2024)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Nyelv: Angol | </span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:black" title="10.1088/1742-6596/2791/1/012060" target="_blank" href="https://doi.org/10.1088/1742-6596/2791/1/012060"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:black" title="85199257327" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85199257327"> Scopus </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:black" title="https://iopscience.iop.org/article/10.1088/1742-6596/2791/1/012060" target="_blank" href="https://iopscience.iop.org/article/10.1088/1742-6596/2791/1/012060"> Egyéb URL </a> </span> </span> <div class="publication-citation"> <a target="_blank" href="/api/publication?cond=citations.related;eq;35141484&sort=publishedYear,desc&sort=title"> Idézett közlemények száma: 1 </a> </div> <div class="mtid"><span class="long-pub-mtid">Közlemény: 35141484</span> | <span class="status-data status-VALIDATED"> Egyeztetett </span> Idéző | <span class="type-subtype">Folyóiratcikk ( Konferenciaközlemény ) </span> | <span class="pub-category">Tudományos</span> | <span class="publication-sourceOfData">kézi felvitel</span> </div> <div class="lastModified">Utolsó módosítás: 2025.03.19. 15:25 Pécsi Éva (MTMT Közp 2,3, admin) </div> </div></div>