03772oam 2200745I 450 991045955710332120200520144314.00-429-14085-11-282-90231-897866129023141-4200-7262-510.1201/EBK1420072617 (CKB)2670000000048315(EBL)589914(OCoLC)669043547(SSID)ssj0000426937(PQKBManifestationID)11290105(PQKBTitleCode)TC0000426937(PQKBWorkID)10404723(PQKB)11252523(MiAaPQ)EBC589914(CaSebORM)9781420072624(Au-PeEL)EBL589914(CaPaEBR)ebr10417844(CaONFJC)MIL290231(OCoLC)671749804(EXLCZ)99267000000004831520180331d2010 uy 0engur|n|---|||||txtccrRelational data clustering models, algorithms, and applications /Bo Long, Zhongfei Zhang, Philip S. Yu1st editionBoca Raton :Chapman & Hall/CRC,2010.1 online resource (214 p.)Chapman & Hall/CRC data mining and knowledge discovery seriesDescription based upon print version of record.1-4665-2984-9 1-4200-7261-7 Includes bibliographical references and index.Front cover; Contents; List of Tables; List of Figures; Preface; Chapter 1: Introduction; Part I: Models; Chapter 2: Co-Clustering; Chapter 3: Heterogeneous Relational Data Clustering; Chapter 4: Homogeneous Relational Data Clustering; Chapter 5: General Relational Data Clustering; Chapter 6: Multiple-View Relational Data Clustering; Chapter 7: Evolutionary Data Clustering; Part II: Algorithms; Chapter 8: Co-Clustering; Chapter 9: Heterogeneous Relational Data Clustering; Chapter 10: Homogeneous Relational Data Clustering; Chapter 11: General Relational Data ClusteringChapter 12: Multiple-View Relational Data ClusteringChapter 13: Evolutionary Data Clustering; Part III: Applications; Chapter 14: Co-Clustering; Chapter 15: Heterogeneous Relational Data Clustering; Chapter 16: Homogeneous Relational Data Clustering; Chapter 17: General Relational Data Clustering; Chapter 18: Multiple-View and Evolutionary Data Clustering; Part IV: Summary; References; Index; Back coverThis is the first book available that presents a comprehensive overview of relational data clustering in data mining research. The book reflects the recent emergence of relational data clustering as an important field of data clustering, with applications in text mining, social network analysis, collaborative filtering, and bioinformatics. It presents an in-depth, systematic discussion of the models, algorithms, and applications for relational data clustering. The book also covers recently emerging models in relational data clustering, including graph-based models, matrix factorization-based mChapman & Hall/CRC data mining and knowledge discovery series.Cluster analysisData miningRelational databasesElectronic books.Cluster analysis.Data mining.Relational databases.005.75/6006.312Long Bo887158Zhang Zhongfei892384Yu Philip S892385MiAaPQMiAaPQMiAaPQBOOK9910459557103321Relational data clustering1992876UNINA