Recent Applications in Data Clustering
Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. The book Recent Applications in Data Clustering aims to provide an outlook of recent contributi...
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| Formato: | Libro |
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IntechOpen
2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=4007304&site=ehost-live header: @attributes: shortDbName: nlebk uiTerm: 4007304 longDbName: eBook Collection (EBSCOhost) uiTag: AN controlInfo: bkinfo: btl: Recent Applications in Data Clustering aug: au: Harun Pirim isbn: 9781789235265 9781838815608 imageinfo: pubinfo: dt: @attributes: year: 2018 month: 01 day: 01 dtAvail: @attributes: year: 2024 month: 10 day: 04 pub: IntechOpen pubContract: Intech Open place: London, United Kingdom price: 0.01 limitsGroup: maxCheckoutDays: 1500 pda: N printPagesOffline: 100 printPagesOnline: 100 previewPages: 10000 prePubGroup: dewey: @attributes: class: 006.312 item: 006 .312 lc: @attributes: class: QA76.9.D343 item: QA 76 .9 .D343 artinfo: ui: 4007304 1454132196 formats: fmt: @attributes: type: EB doid: NL$4007304$PDF caption: PDF download: Y tig: atl: Recent Applications in Data Clustering ptl: Recent Applications in Data Clustering aug: au: Harun Pirim su: Cluster analysis Data mining sug: subj: COMPUTERS / Data Science / Data Analytics Cluster analysis Data mining ab: Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. The book Recent Applications in Data Clustering aims to provide an outlook of recent contributions to the vast clustering literature that offers useful insights within the context of modern applications for professionals, academics, and students. The book spans the domains of clustering in image analysis, lexical analysis of texts, replacement of missing values in data, temporal clustering in smart cities, comparison of artificial neural network variations, graph theoretical approaches, spectral clustering, multiview clustering, and model-based clustering in an R package. Applications of image, text, face recognition, speech (synthetic and simulated), and smart city datasets are presented. pubtype: eBook doctype: Book ougenre: Book language: English copyright: @attributes: flag: N copyrightText: holdings: @attributes: islocal: N |
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