| 書目名稱 | Modern Algorithms of Cluster Analysis | | 編輯 | Slawomir‘Wierzchoń,Mieczyslaw K?opotek | | 視頻video | http://file.papertrans.cn/637/636903/636903.mp4 | | 概述 | Provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, and cluster analysis.Presents a number of approaches to handling a large number of objects | | 叢書名稱 | Studies in Big Data | | 圖書封面 |  | | 描述 | .This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc..?.The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem..?.Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented..?.In addition, the book provides an overview of approaches to handling large collec | | 出版日期 | Book 2018 | | 關(guān)鍵詞 | Cluster Analysis; Big Data; Data Sets; Spectral Clustering; Combinatorial Cluster Analysis | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-69308-8 | | isbn_softcover | 978-3-319-88752-4 | | isbn_ebook | 978-3-319-69308-8Series ISSN 2197-6503 Series E-ISSN 2197-6511 | | issn_series | 2197-6503 | | copyright | Springer International Publishing AG 2018 |
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