ABSTRACT

Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents

chapter 1|6 pages

Knowledge Discovery from Data Streams

chapter 2|26 pages

Introduction to Data Streams

chapter 3|16 pages

Change Detection

chapter 4|14 pages

Maintaining Histograms from Data Streams

chapter 5|16 pages

Evaluating Streaming Algorithms

chapter 6|18 pages

Clustering from Data Streams

chapter 7|18 pages

Frequent Pattern Mining

chapter 8|18 pages

Decision Trees from Data Streams

chapter 9|20 pages

Novelty Detection in Data Streams

chapter 10|14 pages

Ensembles of Classifiers

chapter 11|18 pages

Time Series Data Streams

chapter 12|20 pages

Ubiquitous Data Mining

chapter 13|4 pages

Final Comments