Free Delivery Over $100
|
|
|||
|
||||
OverviewFull Product DetailsAuthor: Ihab F. Ilyas , Xu ChuPublisher: Association of Computing Machinery,U.S. Imprint: Association of Computing Machinery,U.S. Dimensions: Width: 19.10cm , Height: 1.80cm , Length: 23.50cm Weight: 0.699kg ISBN: 9781450371520ISBN 10: 1450371523 Pages: 282 Publication Date: 30 June 2019 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsPreface Figure and Table Credits Introduction Outlier Detection Data Deduplication Data Transformation Data Quality Rule Definition and Discovery Rule-Based Data Cleaning Machine Learning and Probabilistic Data Cleaning Conclusion and Future Thoughts References Index Author BiographiesReviewsAuthor InformationIhab F. Ilyas is a professor in the Cheriton School of Computer Science and the NSERC-Thomson Reuters Research Chair on data quality at the University of Waterloo. His main research focuses on the areas of big data and database systems, with special interest in data quality and integration, managing uncertain data, rank-aware query processing, and information extraction. Ihab is also a co-founder of Tamr, a startup focusing on largescale data integration and cleaning. He is a recipient of the Ontario Early Researcher Award (2009), a Cheriton Faculty Fellowship (2013), an NSERC Discovery Accelerator Award (2014), and a Google Faculty Award (2014), and he is an ACM Distinguished Scientist. Ihab is an elected member of the VLDB Endowment board of trustees, elected SIGMOD vice chair, and an associate editor of the ACM Transactions of Database Systems (TODS). He holds a Ph.D. in Computer Science from Purdue University, West Lafayette. Xu Chu is a tenure-track assistant professor in the School of Computer Science at Georgia Institute of Technology. He obtained his Ph.D. from the University of Waterloo in 2017. His research interests resolve around two themes: using data management technologies to make machine learning more usable, and using machine learning to tackle hard data management problems such as data integration. He won the Microsoft Research Ph.D. Fellowship in 2015. He also received the Cheriton Fellowship from the University of Waterloo, 2013–2015. Tab Content 6Author Website:Countries AvailableAll regions |
||||
