Stream Data Mining
Academic Year 2015/2016
Lecturer:
Annalisa Appice
Lecture notes:
PART I (DATA STREAMS)
1.
Introduction (June 16, 2016)
2.
Data Synopsis (June 17, 2016)
3.Stream Data Mining
3.1.
Classification and regression
3.2.
Clustering
3.3.
Frequent pattern discovery
PART II (SENSOR DATA)
4.
Introduction
5.
Trend cluster discovery
5.1.Summarization
5.2.Interpolation
5.3.Outlier detection and classification
6.
Interpolative clustering
7.
Spatial-aware forecasting
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