Behavioral Pattern Detection Using Compact and Fast Methods
UNIVERSIDADE TÉCNICA DE LISBOA INSTITUTO SUPERIOR TÉCNICO Behavioral Pattern Detection using Compact and Fast Methods Nuno Filipe Lopes Homem Supervisor: Doctor João Paulo Baptista de Carvalho Thesis approved in public session to obtain the PhD Degree in Electrical and Computer Engineering Jury final classification: Pass with Merit Jury Chairperson: Chairman of the IST Scientific Board Members of the Committee: Doctor THOMAS ALFRED RUNKLER, Honorary Professor, Technical University of Munich, Germany Doctor PEDRO MANUEL URBANO DE ALMEIDA LIMA, Professor Associado (Com Agregação), Insituto Superior Técnico, Universidade Técnica de Lisboa Doctor JOÃO MIGUEL DA COSTA SOUSA, Professor Associado (Com Agregação), Insituto Superior Técnico, Universidade Técnica de Lisboa Doctor PEDRO ALEXANDRE MOGADOURO DO COUTO, Professor Auxiliar, Escola de Ciência e Tecnologia, Universidade de Trás-os-Montes e Alto Douro Doctor NUNO CAVACO GOMES HORTA, Professor Auxiliar, Insituto Superior Técnico, Universidade Técnica de Lisboa Doctor JOÃO PAULO BAPTISTA DE CARVALHO, Professor Auxiliar, Instituto Superior Técnico, Universidade Técnica de Lisboa November 2011 Behavioral Pattern Detection using Compact and Fast Methods Abstract This work proposes algorithms and methods for individual behavior detection within very large populations. One will consider domains where individual behavior presents some stable characteristics over time, and where the individual actions can be observed through events in a data stream. Event patterns will be characterized and used as a proxy to individual behavior and actions. As in many domains, behavior does not remain static but evolves over time; one will therefore consider the sliding window model, making the assumption that behavior is stable during the considered time window. This work will cover the detection of the specific characteristics of the individual and what distinguishes his behavior from that of all other individuals.
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