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Jiawei Han

Mining Heterogeneous Information Networks

Principles and Methodologies

Buch

Real-world physical and abstract data objects are interconnected, forming gigantic, interconnected networks. By structuring these data objects and interactions between these objects into multiple types, such networks become semi-structured heterogeneous information networks. Most real-world applications that handle big data, including interconnected social media and social networks, scientific, engineering, or medical information systems, online e-commerce systems, and most database systems, can be structured into heterogeneous information networks. Therefore, effective analysis of large-scale heterogeneous information networks poses an inter… Mehr

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Produktdetails


Weitere Autoren: Sun, Yizhou
  • ISBN: 978-3-031-00774-3
  • EAN: 9783031007743
  • Produktnummer: 39048698
  • Verlag: Springer International Publishing
  • Sprache: Englisch
  • Erscheinungsjahr: 2012
  • Seitenangabe: 212 S.
  • Masse: H27.9 cm x B21.6 cm x D1.1 cm 545 g
  • Abbildungen: Paperback
  • Gewicht: 545

Über den Autor


Yizhou Sun received her Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 2012. She will be an assistant professor in the College of Computer and Information Science at Northeastern University. Her principal research interest is in mining information and social networks, and more generally in data mining, database systems, statistics, machine learning, information retrieval, and network science, with a focus on modeling novel problems and proposing scalable algorithms for large-scale, real-world applications. Yizhou has over 30 publications in books, journals, and major conferences. Tutorials based on her thesis work on mining heterogeneous information networks have been given in several premier conferences, including EDBT 2009, SIGMOD 2010, KDD 2010, ICDE 2012, VLDB 2012, and ASONAM 2012. She received ACM KDD 2012 Best Student Paper Award.Jiawei Han is the Abel Bliss Professor of Computer Science at the University of Illinois at Urbana-Champaign. His research includes data mining, information network analysis, database systems, and data warehousing, with over 600 journal and conference publications. He has chaired or served on many program committees of international conferences, including PC co-chair for KDD, SDM, and ICDM conferences, and Americas Coordinator for VLDB conferences. He also served as the founding Editor-In-Chief of ACM Transactions on Knowledge Discovery from Data and is serving as the Director of Information Network Academic Research Center supported by U.S. Army Research Lab. He is Fellow of ACM and Fellow of IEEE, and received 2004 ACM SIGKDD Innovations Award, 2005 IEEE Computer Society Technical Achievement Award, 2009 IEEE Computer Society Wallace McDowell Award, and 2011 Daniel C. Drucker Eminent Faculty Award at UIUC. His book, Data Mining: Concepts and Techniques, has been used popularly as a textbook worldwide.

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