Mining Heterogeneous Information Networks

Principles and Methodologies

Häftad, Engelska, 2012

469 kr

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Departing from many existing network models that view interconnected data as homogeneous graphs or networks, our semi-structured heterogeneous information network model leverages the rich semantics of typed nodes and links in a network and uncovers surprisingly rich knowledge from the network.

Produktinformation

Utgivningsdatum2012-07-23
Mått216 x 279 x 12 mm
Vikt545 g
FormatHäftad
SpråkEngelska
SerieSynthesis Lectures on Data Mining and Knowledge Discovery
Antal sidor196
FörlagSpringer International Publishing AG
ISBN9783031007743
OriginaltitelMining Heterogeneous Information Networks

Tillhör följande kategorier

Matematisk statistik inom Naturvetenskap och teknik
Systemvetenskap och AI inom Data och IT
Databaser inom Data och IT

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.