El Renacimiento de la Sociología

El potencial de las metodologías informáticas para la sociología se hace cada vez más evidente, así como es cada vez más evidente que la sociología misma está cada vez más inmersa en una sociedad del conocimiento, cuyo combustible principal es la información y su estructuración reflexiva y comunicacional. Las metodologías de investigación y de producción de conocimiento sociológico vinculado al mundo de la información digital computable implican una gama de desafíos presentes y futuros, sobre todo, ante nuevos moldeados de descubrimiento y producción de conocimientos que tienen como soporte las computadoras

Toward autonomic distributed data mining using intelligent web services.

This study defines a new approach for building a Web Services based infrastructure for distributed data mining applications. The proposed architecture provides a roadmap for autonomic functionality of the infrastructure hiding the complexity of implementation details and enabling the user with a new level of usability in data mining process. Web Services based infrastructure delivers all required data mining activities in a utility-like fashion enabling heterogeneous components to be incorporated in a unified manner. Moreover, this structure allows the implementation of data mining algorithms for processing data on more than one source in a distributed manner. The purpose of this study is to present a simple, but efficient methodology for determining when data distributed at several sites can be centralized and analyzed as data from the same theoretical distribution. This analysis also answers when and how the semantics of the sites is influenced by distribution in data. This hierarchical framework with advanced and core Web Services improves the current data mining capability significantly in terms of performance, scalability, efficiency, transparency of resources, and incremental extensibility

Um método de tradução de fontes de informação em um formato padrão que viabilize a extração de conhecimento por meio de link analysis e teoria dos grafos

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.O conhecimento tem se configurado como um recurso estratégico nas organizações. Para elas, gerar, codificar, gerir e disseminar o conhecimento organizacional tornaram-se tarefas essenciais. Logo, é necessário o desenvolvimento de novas técnicas, metodologias e formas de extração de conhecimento a partir de fontes de informação que descrevem um domínio de aplicação. Nesse contexto, o objetivo do presente trabalho é propor um método que permita traduzir fontes de informação em um formato padrão de representação de relacionamentos entre elementos do domínio do problema, de forma a viabilizar a extração de conhecimento por meio da aplicação de Link Analysis e Teoria dos Grafos. Além disso, são apresentadas duas aplicações desse modelo na Plataforma Lattes de CT&I

From Dataveillance to Data Economy: Firm View on Data Protection

The increasing availability of electronic records and the expanded reliance on online communications and services have made available a huge amount of data about people’s behaviours, characteristics, and preferences. Advancements in data processing technology, known as big data, offer opportunities to increase organisational efficiency and competitiveness. Analytically sophisticated companies excel in their ability to extract value from the analysis of digital data. However, in order to exploit the potential economic benefits produced by big data and analytics, issues of data privacy and information security need to be addressed. In Europe, organisations processing personal data are being required to implement basic data protection principles, which are considered difficult to implement in big data environments. Little is known in the privacy studies literature about how companies manage the trade-off between data usage and data protection. This study contributes to explore the corporate data privacy environment, by focusing on the interrelationship between the data protection legal regime, the application of big data analytics to achieve corporate objectives, and the creation of an organisational privacy culture. It also draws insights from surveillance studies, particularly the idea of dataveillance, to identify potential limitations of the current legal privacy regime. The findings from the analysis of survey data show that big data and data protection support each other, but also that some frictions can emerge around data collection and data fusion. The demand for the integration of different data sources poses challenges to the implementation of data protection principles. However, this study finds no evidence that data protection laws prevent data gathering. Implications relevant for the debate on the reform of European data protection law are also drawn from these findings

Critical Success Factors in Data Mining Projects.

The increasing awareness of data mining technology, along with the attendant increase in the capturing, warehousing, and utilization of historical data to support evidence-based decision making, is leading many organizations to recognize that the effective use of data is the key element in the next generation of client-server enterprise information technology. The concept of data mining is gaining acceptance in business as a means of seeking higher profits and lower costs. To deploy data mining projects successfully, organizations need to know the key factors for successful data mining. Implementing emerging information systems (IS) can be risky if the critical success factors (CSFs) have been researched insufficiently or documented inadequately. While numerous studies have listed the advantages and described the data mining process, there is little research on the success factors of data mining. This dissertation identifies CSFs in data mining projects. Chapter 1 introduces the history of the data mining process and states the problems, purposes, and significances of this dissertation. Chapter 2 reviews the literature, discusses general concepts of data mining and data mining project contexts, and reviews general concepts of CSF methodologies. It also describes the identification process for the various CSFs used to develop the research framework. Chapter 3 describes the research framework and methodology, detailing how the CSFs were identified and validated from more than 1,300 articles published on data mining and related topics. The validated CSFs, organized into a research framework using 7 factors, generate the research questions and hypotheses. Chapter 4 presents analysis and results, along with the chain of evidence for each research question, the quantitative instrument and survey results. In addition, it discusses how the data were collected and analyzed to answer the research questions. Chapter 5 concludes with a summary of the findings, describing assumptions and limitations and suggesting future research

Multi-signal gesture recognition using body and hand poses

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 147-154).We present a vision-based multi-signal gesture recognition system that integrates information from body and hand poses. Unlike previous approaches to gesture recognition, which concentrated mainly on making it a signal signal, our system allows a richer gesture vocabulary and more natural human-computer interaction. The system consists of three parts: 3D body pose estimation, hand pose classification, and gesture recognition. 3D body pose estimation is performed following a generative model-based approach, using a particle filtering estimation framework. Hand pose classification is performed by extracting Histogram of Oriented Gradients features and using a multi-class Support Vector Machine classifier. Finally, gesture recognition is performed using a novel statistical inference framework that we developed for multi-signal pattern recognition, extending previous work on a discriminative hidden-state graphical model (HCRF) to consider multi-signal input data, which we refer to Multi Information-Channel Hidden Conditional Random Fields (MIC-HCRFs). One advantage of MIC-HCRF is that it allows us to capture complex dependencies of multiple information channels more precisely than conventional approaches to the task. Our system was evaluated on the scenario of an aircraft carrier flight deck environment, where humans interact with unmanned vehicles using existing body and hand gesture vocabulary. When tested on 10 gestures recorded from 20 participants, the average recognition accuracy of our system was 88.41%.by Yale Song.S.M

A MODEL OF ORGANIZATIONAL COMPETENCIES FOR BUSINESS INTELLIGENCE SUCCESS

Business intelligence (BI) systems comprise one of the largest and fastest growing areas of IT expenditure in companies today. Companies’ experiences with deriving benefits from these systems are still mixed. One of the differences between BI and other types of information systems is that how BI systems are used, not just whether they are used, can have a major impact on the benefits derived. Therefore the characteristics of BI users and the organizations within which they work can have a disproportionate impact on the benefits derived from investments in BI. Organizational competence is one way to evaluate the characteristics of individuals and organizations relative to their ability to achieve organizational goals. This dissertation examines the characteristics of BI users and their organizations within the framework of organizational competences. Models representing those competences at both the individual and organizational level are presented. A combined competency model and resulting emerging competences are proposed that, if adopted, can improve the likelihood of organizations realizing benefits from their BI investments

Um estudo da Diabetes Mellitus e Hipertensão Arterial baseado em técnicas de Data Mining aplicadas a dados da Administração Regional de Saúde do Centro

Esta dissertação resulta de um acordo de colaboração entre a Administração Regional de Saúde do Centro e o Instituto Superior de Engenharia de Coimbra do Instituto Politécnico de Coimbra, e visa estudar os dados sobre as doenças Diabetes Mellitus e Hipertensão, aplicando métodos de Tecnologias da Informação e do Conhecimento, integrados na área científica de Business Intelligence e Data Mining. Na atualidade, a Diabetes Mellitus e Hipertensão são patologias incuráveis e o número de pessoas afetadas continua a agravar-se. Existe um forte interesse em abordagens realizáveis e de custo suportável, especialmente em casos não diagnosticados, para intervenção o mais cedo possível. Existe interesse em encontrar sistemas de identificação de pacientes sem recorrer a testes bioquímicos. Com a proliferação das Tecnologias de Informação na sociedade, desenvolver a baixo custo e de acesso generalizado pode fazer decrescer o número de pacientes não diagnosticados. As ferramentas devem auxiliar o processo de identificar quem poderá ser afetado para reduzir riscos preventivamente. O uso das Tecnologias de Informação pelos prestadores de cuidados de saúde em conjunto com educação dos pacientes resultará em benefícios significativos na luta contra estas doenças crónicas. É neste segmento que este estudo se inclui, adicionando as tecnologias de informação às abordagens tradicionais. Neste trabalho aplicam-se técnicas de Data Mining para extrair conhecimento dos dados existentes no Data Warehouse da Administração Regional de Saúde do Centro. A primeira parte carateriza as doenças para determinar quais os seus aspetos mais relevantes a considerar no desenvolvimento das restantes tarefas. A segunda parte carateriza métodos e metodologias de Data Mining com o intuito de descrever as tarefas e técnicas utilizadas. Existem atualmente diversas ferramentas que implementam os diversos algoritmos de extração do conhecimento pelo que na terceira parte do trabalho é realizada uma comparação com vista à seleção informada e esclarecida da ferramenta base a utilizar neste estudo. A quarta parte é baseada nos passos comuns das metodologias aplicáveis aos estudos deste género e que consiste em compreender os dados, preparar os dados, proceder à sujeição dos dados aos algoritmos e avaliar os resultados dos modelos inferidos. A última etapa do estudo elabora algumas conclusões e sugere trabalho futuro. A saúde é, por natureza, de importância vital para o ser humano. Devemos, por isso, evidenciar todos os esforços possíveis para que novo conhecimento possa ser gerado e usado

A component framework for personalized multimedia applications

Eine praktikable Unterstützung für eine dynamische Erstellung von personalisierten Multimedia-Präsentationen bieten bisher weder industrielle Lösungen noch Forschungsansätze. Mit dem Software-technischen Ansatz des MM4U-Frameworks („MultiMedia For You“) wird erstmals eine generische und zugleich praktikable Unterstützung für den dynamischen Erstellungsprozess bereitgestellt. Das Ziel des MM4U-Frameworks ist es den Anwendungsentwicklern eine umfangreiche und anwendungsunabhängige Unterstützung zur Erstellung von personalisierten Multimedia-Inhalten anzubieten und damit den Entwicklungsprozess solcher Anwendungen erheblich zu erleichtern. Um das Ziel eines Software-Frameworks zur generischen Unterstützung der Entwicklung von personalisierten Multimedia-Anwendungen zu erreichen, stellt sich die Frage nach einer geeigneten Software-technischen Unterstützung zur Entwicklung eines solchen Frameworks. Seit der Einführung von objektorientierten Frameworks, ist heute die Entwicklung immer noch aufwendig und schwierig. Um die Entwicklungsrisiken zu reduzieren, sind geeignete Vorgehensmodelle und Entwicklungsmethoden erstellt worden. Mit der Komponenten-Technologie sind auch so genannte Komponenten-Frameworks entstanden. Im Gegensatz zu objekt-orientierten Frameworks fehlt derzeit jedoch ein geeignetes Vorgehensmodell für Komponenten-Frameworks. Um den Entwicklungsprozess von Komponenten-Frameworks zu verbessern ist mit ProMoCF („Process Model for Component Frameworks“) ein neuartiger Ansatz entwickelt worden. Hierbei handelt es sich um ein leichtgewichtiges Vorgehensmodell und eine Entwicklungsmethodik für Komponenten-Frameworks. Das Vorgehensmodell wurde unter gegenseitigem Nutzen mit der Entwicklung des MM4U-Frameworks erstellt. Das MM4U-Framework stellt keine Neuerfindung der Adaption von Multimedia-Inhalten dar, sondern zielt auf die Vereinigung und Einbettung existierender Forschungsansätze und Lösungen im Umfeld der Multimedia-Personalisierung. Mit so einem Framework an der Hand können Anwendungsentwickler erstmals effizient und einfach eine dynamische Erstellung ihrer personalisierten Multimedia-Inhalte realisieren