Event mining: algorithms and applications
Series: Chapman & Hall/CRC data mining and knowledge discovery seriesPublication details: Boca Raton CRC Press 2016Description: xxv, 308 pISBN:- 9781466568570
- 006.312 E9
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Ahmedabad | Non-fiction | 006.312 E9 (Browse shelf(Opens below)) | Available | 192284 |
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006.312 B7P7-2013 Principles of data mining | 006.312 B8L3 Learning classifier systems in data mining | 006.312 D2 Data mining: foundations and practice | 006.312 E9 Event mining: algorithms and applications | 006.312 G2K6 Knowledge discovery from data streams | 006.312 H3D2 Data literacy: a user's guide | 006.312 H8 The human element of big data: issues, analytics and performance |
Table of Contents:
1. Introduction
Part I - Event Generation and System Monitoring
2. Event Generation: From Logs to Events
3. Optimizing System Monitoring Configurations
Part II - Pattern Discovery and Summarization
4. Event Pattern Mining
5. Mining Time Lags
6. Log Event Summarization
Part III – Applications
7. Data-Driven Applications in System Management
8. Social Media Event Summarization Using Twitter Streams
Event mining encompasses techniques for automatically and efficiently extracting valuable knowledge from historical event/log data. The field, therefore, plays an important role in data-driven system management. Event Mining: Algorithms and Applications presents state-of-the-art event mining approaches and applications with a focus on computing system management.
The book first explains how to transform log data in disparate formats and contents into a canonical form as well as how to optimize system monitoring. It then shows how to extract useful knowledge from data. It describes intelligent and efficient methods and algorithms to perform data-driven pattern discovery and problem determination for managing complex systems. The book also discusses data-driven approaches for the detailed diagnosis of a system issue and addresses the application of event summarization in Twitter messages (tweets).
Understanding the interdisciplinary field of event mining can be challenging as it requires familiarity with several research areas and the relevant literature is scattered in diverse publications. This book makes it easier to explore the field by providing both a good starting point for readers not familiar with the topics and a comprehensive reference for those already working in this area.
(https://www.crcpress.com/Event-Mining-Algorithms-and-Applications/Li/p/book/9781466568570)
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