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Martin Atzmüller

    Knowledge-intensive subgroup mining
    Analysis of social media and ubiquitous data
    Modeling and mining ubiquitous social media
    Ubiquitous social media analysis
    Big Data Analytics in the Social and Ubiquitous Context
    Lohnsteuertabellen 2023
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      Lohnsteuertabellen 2023
    • Big Data Analytics in the Social and Ubiquitous Context

      5th International Workshop on Modeling Social Media, MSM 2014, 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers

      • 196 Seiten
      • 7 Lesestunden

      The 9 papers presented in this book are revised and significantly extended versions of papers submitted to three related workshops: The 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and the First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, which were held on September 15, 2014, in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2014) in Nancy, France; and the 5th International Workshop on Modeling Social Media (MSM 2014) that was held on April 8, 2014 in conjunction with ACM WWW in Seoul, Korea.

      Big Data Analytics in the Social and Ubiquitous Context
    • Ubiquitous social media analysis

      • 185 Seiten
      • 7 Lesestunden

      This book constitutes the thoroughly refereed joint post-proceedings of the Third International Workshop on Mining Ubiquitous and Social Environments, MUSE 2012, held in Bristol, UK, in September 2012, and the Third International Workshop on Modeling Social Media, MSM 2012, held in Milwaukee, WI, USA, in June 2012. The 8 full papers included in the book are revised and significantly extended versions of papers submitted to the workshops. They cover a wide range of topics organized in three main themes: communities and group structure in ubiquitous social media; ubiquitous modeling and aspects of social interactions and influence.

      Ubiquitous social media analysis
    • This book constitutes the joint thoroughly refereed post-proceedings of the Second International Workshop on Modeling Social Media, MSM 2011, held in Boston, MA, USA, in October 2011, and the Second International Workshop on Mining Ubiquitous and Social Environments, MUSE 2011, held in Athens, Greece, in September 2011. The 9 full papers included in the book are revised and significantly extended versions of papers submitted to the workshops. They cover a wide range of topics organized in three main themes: communities and networks in ubiquitous social media; mining approaches; and issues of user modeling, privacy and security.

      Modeling and mining ubiquitous social media
    • This book constitutes the joint thoroughly refereed post-proceedings of The Modeling Social Media Workshop, MSM 2010 held in Toronto, Canada in June 2010 and the International Workshop on Mining Ubiquitous and Social Environments, MUSE 2010, held in Barcelona, Spain in September 2010. The eight revised full papers included were carefully reviewed and selected after two rounds of reviewing and revision. The papers address various aspects of the analysis and engineering of socio-computational systems in which social, ubiquitous and computational processes are interdependent and tightly interwoven

      Analysis of social media and ubiquitous data
    • Subgroup mining is a powerful data mining approach aimed at discovering novel and useful knowledge through subgroup patterns. However, real-world applications often face challenges such as scalability issues with large datasets, overwhelming results, and the prevalence of already known patterns. This thesis introduces a combination of techniques to address these challenges. It presents the SD-Map algorithm, which is both fast and effective for automatic methods. Additionally, it describes interactive techniques for subgroup introspection and analysis, along with advanced visualization methods for subgroup optimization, comparison, and exploration. The approach also incorporates various classes and types of background knowledge into the mining process, creating a knowledge-intensive framework that supports both automatic and interactive methods. The evaluation comprises two parts: an objective assessment of efficiency and effectiveness through thorough experimental evaluation using synthetic data, and a subjective assessment focusing on user acceptance, benefits, and the interestingness of results. The proposed methods have been successfully implemented in medical and technical applications, with five case studies utilizing real-world data demonstrating their effectiveness.

      Knowledge-intensive subgroup mining