Session details: Theme: Information systems: DS - Data streams track

• DOI: 10.1145/3329367
• Publication Date: 2020-04-24T10:44:23Z
• Authors: Albert Bifet; André C. P. L. F....; Carlos Ferreira; João Gama
• Keywords: Stream Processing

The rapid growth in data science and technology, particular the complexity volume of Big Data, has introduced new challenges for research community. Several these are related to nature generation, since most sources produce continuously. Examples include sensor wireless networks, radio frequency identification, customer click streams, telephone records, multimedia scientific data, sets retail chain transactions, among others. These called ordered sequences instances that can typically be read only once or a small number times due its their high speed flow continuous nature. Data streams characterized by being open-ended, generated non-stationary distributions. Thus, they increasingly important community, as algorithms needed efficiently process this streaming enable real-time updated understanding data. goal track is convene researchers who work with defining models, processing queries, developing sampling, filtering stream mining methods, machine learning, visualization techniques issues.