Outlier Detection: A Data Mining Perspective (1st ed. 2019) (Intelligent Systems Reference Library #155)
By: and and
Sign Up Now!
Already a Member? Log In
You must be logged into Bookshare to access this title.
Learn about membership options,
or view our freely available titles.
- Synopsis
- This book, drawing on recent literature, highlights several methodologies for the detection of outliers and explains how to apply them to solve several interesting real-life problems. The detection of objects that deviate from the norm in a data set is an essential task in data mining due to its significance in many contemporary applications. More specifically, the detection of fraud in e-commerce transactions and discovering anomalies in network data have become prominent tasks, given recent developments in the field of information and communication technologies and security. Accordingly, the book sheds light on specific state-of-the-art algorithmic approaches such as the community-based analysis of networks and characterization of temporal outliers present in dynamic networks. It offers a valuable resource for young researchers working in data mining, helping them understand the technical depth of the outlier detection problem and devise innovative solutions to address related challenges.
- Copyright:
- 2019
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783030051273
- Related ISBNs:
- 9783030051259
- Publisher:
- Springer International Publishing
- Date of Addition:
- 01/11/19
- Copyrighted By:
- Springer
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Science, Computers and Internet
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
Reviews
Other Books
- by N. N. Ranga Suri
- by Narasimha Murty M
- by G. Athithan
- in Nonfiction
- in Science
- in Computers and Internet