Mining data streams under block evolution

作者：Venkatesh Ganti, Johannes E. Gehrke, Raghu Ramakrishnan · 发表于：ACM SIGKDD Explorations Newsletter · 年份：2002 · DOI：10.1145/507515.507517 · 被引用次数：132 · 研究领域：Data Stream Mining Techniques、Algorithms and Data Compression、Evolutionary Algorithms and Applications

In this paper we survey recent work on incremental data mining model maintenance and change detection under block evolution. In block evolution, a dataset is updated periodically through insertions and deletions of blocks of records at a time. We describe two techniques: (1) We describe a generic algorithm for model maintenance that takes any traditional incremental data mining model maintenance algorithm and transforms it into an algorithm that allows restrictions on a temporal subset of the database. (2) We also describe a generic framework for change detection, that quantifies the difference between two datasets in terms of the data mining models they induce.