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1 - 8 of 8
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Computing with data: an introduction to the data industry
Lebanon G., El-Geish M., Springer International Publishing, New York, NY, 2018. 576 pp. Type: Book (978-3-319981-48-2)
This book is envisioned as a companion volume on modern cloud computing. However, it is too broad, and in my opinion provides only superficial coverage of many subjects. It is certainly a deliberate (and courageous) decision by the aut...
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Oct 11 2019 |
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Principles of database management: the practical guide to storing, managing and analyzing big and small data
Lemahieu W., vanden Broucke S., Baesens B., Cambridge University Press, New York, NY, 2018. 808 pp. Type: Book (978-1-107186-12-5)
The book maintains a very practical approach to introducing the principles of database management for an undergraduate database management course....
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Apr 9 2019 |
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 Fundamentals of machine learning for predictive data analytics: algorithms, worked examples, and case studies
Kelleher J., Mac Namee B., D’Arcy A., The MIT Press, Cambridge, MA, 2015. 624 pp. Type: Book (978-0-262029-44-5), Reviews: (2 of 4)
Said to be among the most exciting fields in tech, machine learning is a trending topic right now. Machine learning has seen massive innovation and growth in the past decade and has become so pervasive that most of us use it daily with...
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Jan 27 2016 |
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Doing data science: straight talk from the frontline
Schutt R., O’Neil C., O’Reilly Media, Inc., Sebastopol, CA, 2013. 406 pp. Type: Book (978-1-449358-65-5)
Business hype around data science, and more recently, the data science profession, has done surprisingly little to close the gap in understanding how data science is done and the persona that drives its application. For this reason, I ...
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May 16 2014 |
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Detecting evolutionary financial statement fraud
Zhou W., Kapoor G. Decision Support Systems 50(3): 570-575, 2011. Type: Article
Data mining is a leading approach to financial fraud detection; however, its techniques are prone to error and inadequacy. In this paper, Zhou and Kapoor note that, while successful at the beginning, data mining methods are less effect...
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Jun 8 2011 |
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Data mining X: data mining, protection, detection and other security technologies
Zanasi A., Brebbia C., Ebecken N., WIT Press, Southampton, UK, 2009. 208 pp. Type: Book (9781845641849)
This book is a collection of papers presented at the Tenth International Conference on Data Mining. The latest trends in data mining applications and research increasingly deal with text mining and Web mining. These two areas, within t...
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Jan 26 2010 |
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Transaction aggregation as a strategy for credit card fraud detection
Whitrow C., Hand D., Juszczak P., Weston D., Adams N. Data Mining and Knowledge Discovery 18(1): 30-55, 2009. Type: Article
Whitrow et al. investigate the important problem of detecting fraudulent credit card transactions. A traditional approach to detecting a fraudulent transaction is based on a transaction-level classification. Another method is to consid...
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Nov 5 2009 |
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Using checklists to review static analysis warnings
Ayewah N., Pugh W. DEFECTS 2009 (Proceedings of the 2nd International Workshop on Defects in Large Software Systems, Chicago, IL, Jul 19, 2009) 11-15, 2009. Type: Proceedings
Static analysis is important for detecting code defects. Most automatic tools based on static analysis have reached a certain level of maturity, making them trusted partners in code quality assurance. However, the tools are often limit...
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Sep 21 2009 |
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