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.
Cited By
- Wang W, Zeng C and Li T Discovering Multiple Time Lags of Temporal Dependencies from Fluctuating Events Web and Big Data, (121-137)
- Li T, Zeng C, Jiang Y, Zhou W, Tang L, Liu Z and Huang Y (2017). Data-Driven Techniques in Computing System Management, ACM Computing Surveys, 50:3, (1-43), Online publication date: 31-May-2018.
- Ye Y, Li T, Adjeroh D and Iyengar S (2017). A Survey on Malware Detection Using Data Mining Techniques, ACM Computing Surveys, 50:3, (1-40), Online publication date: 31-May-2018.
- Zelst S, Dongen B and Aalst W (2018). Event stream-based process discovery using abstract representations, Knowledge and Information Systems, 54:2, (407-435), Online publication date: 1-Feb-2018.
- Li T, Jiang Y, Zeng C, Xia B, Liu Z, Zhou W, Zhu X, Wang W, Zhang L, Wu J, Xue L and Bao D FLAP Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (1547-1556)
- Zeng C, Zhou W, Li T, Shwartz L and Grabarnik G (2017). Knowledge Guided Hierarchical Multi-Label Classification Over Ticket Data, IEEE Transactions on Network and Service Management, 14:2, (246-260), Online publication date: 1-Jun-2017.
- Jiang Y, Perng C, Sailer A, Silva-Lepe I, Zhou Y and Li T (2016). CSM, ACM Transactions on Intelligent Systems and Technology, 8:1, (1-25), Online publication date: 3-Oct-2016.
Index Terms
- Event Mining: Algorithms and Applications
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