Artículos relacionados a On Uncertain Graphs (Synthesis Lectures on Data Management)
Sinopsis
Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Arijit Khan is an assistant professor in the School of Computer Engineering at Nanyang Technological University, Singapore. His research interests span in the area of big-data, big-graphs, and graph systems. He received his Ph.D. from the Department of Computer Science, University of California, Santa Barbara, and did a post-doc in the Systems group at ETH Zurich. Arijit was the recipient of the prestigious IBM Ph.D. Fellowship in 2012-13. He published several papers in premier database and data-mining conferences and journals including SIGMOD, VLDB, TKDE, ICDE, SDM, EDBT, and CIKM. Arijit co-presented tutorials on emerging graph queries, big-graph systems, summarization, and uncertain graphs at ICDE 2012, VLDB 2014, VLDB 2015, and VLDB 2017, and served in the program committee of KDD, SIGMOD, VLDB, ICDM, EDBT, WWW, and CIKM. Arijit served as the co-chair of Big-O(Q) workshop co-located with VLDB 2015.Yuan Ye is a professor in the Department of Computer Science, Northeastern University, China. His research interests are graph databases, probabilistic databases, social network analysis and big-data computing systems. Yuan Ye received the B.S., M.S., and Ph.D. degrees in Computer Science from Northeastern University in 2004, 2007, and 2011, respectively. He was a visiting scholar of the Hong Kong University of Science and Technology, the Chinese University of Hong Kong, and the University of Edinburgh. Yuan Ye published several papers in premier database conferences and journals including SIGMOD, VLDB, ICDE, CIKM, VLDB Journal, TKDE, and TPDS. He served in the program committee of SIGMOD, VLDB, ICDE, EDBT, and CIKM. Yuan Ye received the award of the CCF excellent doctoral dissertation in 2012 and the excellent youth scholar of NSFC in 2016.Lei Chen received a B.S. in Computer Science and Engineering from Tianjin University, China in 1994, an M.A. from Asian Institute of Technology, Thailand, in 1997, and a Ph.D. in Computer Science from University of Waterloo, Canada in 2005. He is now an associate professor in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology. His research interests include uncertain databases, graph databases, multimedia, and time series databases, and sensor and peer-to-peer databases. He is editor-in-chief of the VLDB Journal and serving as an associate editor for IEEE Transactions on Knowledge and Data Engineering and Distributed and Parallel Databases. He is the PC Co-chair of the 45th International Conference on Very Large Databases (VLDB), 2019, and has served as PC Co-chair, PC Track Chair, and PC member for many conferences. He was awarded the SIGMOD Test of Time Award in 2015. He is a member of the IEEE and ACM.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialSpringer
- Año de publicación2018
- ISBN 10 3031007328
- ISBN 13 9783031007323
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas96
- Contacto del fabricanteno disponible
Comprar nuevo
Ver este artículo
EUR 60,38
EUR 4,71 gastos de envío desde Reino Unido a España
Destinos, gastos y plazos de envíoOtras ediciones populares con el mismo título
Resultados de la búsqueda para On Uncertain Graphs (Synthesis Lectures on Data Management)
Imagen de archivo
On Uncertain Graphs (Synthesis Lectures on Data Management)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. In. Nº de ref. del artículo: ria9783031007323_new
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
On Uncertain Graphs
Publicado por
Berlin Springer International Publishing Springer Jul 2018, 2018
ISBN 10: 3031007328
ISBN 13: 9783031007323
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions. 80 pp. Englisch. Nº de ref. del artículo: 9783031007323
Cantidad disponible: 2 disponibles
Imagen del vendedor
On Uncertain Graphs
Publicado por
Springer, Berlin, Springer International Publishing, Morgan & Claypool, Springer, 2018
ISBN 10: 3031007328
ISBN 13: 9783031007323
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions. Nº de ref. del artículo: 9783031007323
Cantidad disponible: 2 disponibles
Imagen del vendedor
On Uncertain Graphs
Publicado por
Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2018
ISBN 10: 3031007328
ISBN 13: 9783031007323
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 4 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measureme. Nº de ref. del artículo: 608129118
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
On Uncertain Graphs
Librería: Chiron Media, Wallingford, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
PF. Condición: New. Nº de ref. del artículo: 6666-IUK-9783031007323
Cantidad disponible: 10 disponibles
Imagen de archivo
On Uncertain Graphs (Synthesis Lectures on Data Management)
Librería: Books Puddle, New York, NY, Estados Unidos de America
Calificación del vendedor: 4 de 5 estrellas
Condición: New. 1st edition NO-PA16APR2015-KAP. Nº de ref. del artículo: 26395061334
Cantidad disponible: 4 disponibles
Imagen de archivo
On Uncertain Graphs (Synthesis Lectures on Data Management)
Impresión bajo demandaLibrería: Majestic Books, Hounslow, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Print on Demand. Nº de ref. del artículo: 402364297
Cantidad disponible: 4 disponibles
Imagen de archivo
On Uncertain Graphs (Synthesis Lectures on Data Management)
Impresión bajo demandaLibrería: Biblios, Frankfurt am main, HESSE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. PRINT ON DEMAND. Nº de ref. del artículo: 18395061340
Cantidad disponible: 4 disponibles