2004 · 90 citations · 15 references
ComputingData ScienceInformation TechnologyData AnalyticsData ManagementData MiningIncident DetectionIncident ManagementStream ProcessingStreaming AlgorithmsTemporal Data MiningTime Series AnalyticsClusteringData Stream Management SystemsData Stream MiningData Stream ProcessingIncident Detection SystemsStream MiningStream-based Event DetectionStreaming Data Mining
This paper presents a demonstration of our recent research and development of the MAIDS system, which mines alarming incidents from data streams, with the following major analysis functions: (1) multi-resolution modeling using a tilted time window framework, (2) multi-dimensional analysis using a stream “data cube” model, (3) online stream classification, (4) online frequent pattern mining, (5) online clustering of data streams, and (6) stream mining visualization.
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Mining frequent patterns without candidate generation
Jiawei Han, Jian Pei, Yiwen Yin · ACM SIGMOD Record · 2000 · 6.4K citations
Ian H. Witten, Eibe Frank · ACM SIGMOD Record · 2002 · 5.2K citations
Tian Zhang, Raghu Ramakrishnan, Miron Livny · 1996 · 3.9K citations
Mining frequent patterns without candidate generation
Jiawei Han, Jian Pei, Yiwen Yin · 2000 · 3.2K citations · Full text
Models and issues in data stream systems
Brian Babcock, Shivnath Babu, Mayur Datar et al. · 2002 · 2.5K citations