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1	Contributions to Collective Dynamical Clustering-Modeling of Discrete Time Series Wang, Chiying 27 April 2016 (has links) The analysis of sequential data is important in business, science, and engineering, for tasks such as signal processing, user behavior mining, and commercial transactions analysis. In this dissertation, we build upon the Collective Dynamical Modeling and Clustering (CDMC) framework for discrete time series modeling, by making contributions to clustering initialization, dynamical modeling, and scaling. We first propose a modified Dynamic Time Warping (DTW) approach for clustering initialization within CDMC. The proposed approach provides DTW metrics that penalize deviations of the warping path from the path of constant slope. This reduces over-warping, while retaining the efficiency advantages of global constraint approaches, and without relying on domain dependent constraints. Second, we investigate the use of semi-Markov chains as dynamical models of temporal sequences in which state changes occur infrequently. Semi-Markov chains allow explicitly specifying the distribution of state visit durations. This makes them superior to traditional Markov chains, which implicitly assume an exponential state duration distribution. Third, we consider convergence properties of the CDMC framework. We establish convergence by viewing CDMC from an Expectation Maximization (EM) perspective. We investigate the effect on the time to convergence of our efficient DTW-based initialization technique and selected dynamical models. We also explore the convergence implications of various stopping criteria. Fourth, we consider scaling up CDMC to process big data, using Storm, an open source distributed real-time computation system that supports batch and distributed data processing. We performed experimental evaluation on human sleep data and on user web navigation data. Our results demonstrate the superiority of the strategies introduced in this dissertation over state-of-the-art techniques in terms of modeling quality and efficiency. discrete time series deviated dynamic time warping semi-Markov chain distributed data processing system
2	Métodos e softwares para análise da produção científica e detecção de frentes emergentes de pesquisa / Methods and software for scientific production analysis and detection of emerging research trends REIS JUNIOR, JOSE S.B. 21 December 2016 (has links) Submitted by Marco Antonio Oliveira da Silva (maosilva@ipen.br) on 2016-12-21T15:07:24Z No. of bitstreams: 0 / Made available in DSpace on 2016-12-21T15:07:24Z (GMT). No. of bitstreams: 0 / O progresso de projetos anteriores salientou a necessidade de tratar o problema dos softwares para detecção, a partir de bases de dados de publicações científicas, de tendências emergentes de pesquisa e desenvolvimento. Evidenciou-se a carência de aplicações computacionais eficientes dedicadas a este propósito, que são artigos de grande utilidade para um melhor planejamento de programas de pesquisa e desenvolvimento em instituições. Foi realizada, então, uma revisão dos softwares atualmente disponíveis, para poder-se delinear claramente a oportunidade de desenvolver novas ferramentas. Como resultado, implementou-se um aplicativo chamado Citesnake, projetado especialmente para auxiliar a detecção e o estudo de tendências emergentes a partir da análise de redes de vários tipos, extraídas das bases de dados científicas. Através desta ferramenta computacional robusta e eficaz, foram conduzidas análises de frentes emergentes de pesquisa e desenvolvimento na área de Sistemas Geradores de Energia Nuclear de Geração IV, de forma que se pudesse evidenciar, dentre os tipos de reatores selecionados como os mais promissores pelo GIF - Generation IV International Forum, aqueles que mais se desenvolveram nos últimos dez anos e que se apresentam, atualmente, como os mais capazes de cumprir as promessas realizadas sobre os seus conceitos inovadores. / Dissertação (Mestrado em Tecnologia Nuclear) / IPEN/D / Instituto de Pesquisas Energéticas e Nucleares - IPEN-CNEN/SP reactors power generation reactor monitoring systems reactor technology site characterization nuclear engineering computer networks tools technology transfer research programs comparative evaluations data covariances data base management data compilation data tagging distributed data processing documentation information centers information dissemination information retrieval information theory knowledge management performance accuracy specificity tolerance

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Contributions to Collective Dynamical Clustering-Modeling of Discrete Time Series

Métodos e softwares para análise da produção científica e detecção de frentes emergentes de pesquisa / Methods and software for scientific production analysis and detection of emerging research trends