Data Mining in Time Series and Streaming Databases

While most data mining algorithms deal with static data, the seven papers in this collection address systems producing massive high-speed streams of ever-changing data generated by dynamic processes. The contributors report progress on finding the most efficient representation of streaming data, developing privacy-preserving methods for data stream mining, incremental pre-processing of continuous time series and data streams in parallel to the data mining process, handling delayed information, mining entity-related time series, and designing online monitoring systems. Annotation ©2018 Ringgold, Inc., Portland, OR (protoview.com)