ABSTRACT

Data mining is faced with new challenges. All of them share common issues: a continuously flow of data generated by evolving distributions, the domains involved (the set of attribute-values) can also be huge, and computation resources (processing power, storage, bandwidth, and battery power) are limited. In this scenario, data mining approaches involving fixed training sets, static models, stationary distributions, and unrestricted computational resources are almost obsolete.