Communications of the ACM
Communications of the ACM
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
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Data mining is the process of finding patterns in information contained in large databases. It is a research area at the intersection of several disciplines, including statistics, databases, pattern recognition and AI, visualization, optimization, and high-performance and parallel computing. With the success of database systems, and their widespread use, the role of the database expanded from being a reliable data store to being a decision support system (DSS). This has been manifested in the growth of data warehouses that consolidate transactional and distributed databases. Examples of applications of data mining techniques include: fraud detection in banking and telecommunications; marketing; science data analysis involving cataloging objects of interest in large data sets (e.g. sky objects in a survey, volcanoes on Venus, finding atmospheric events in remote sensing data); problem diagnosis in manufacturing, medicine, or networking; and so forth. The techniques are particularly relevant in settings where data is plentiful and the processes generating it are poorly understood.