20,330 research outputs found

    From the User to the Medium: Neural Profiling Across Web Communities

    Full text link
    Online communities provide a unique way for individuals to access information from those in similar circumstances, which can be critical for health conditions that require daily and personalized management. As these groups and topics often arise organically, identifying the types of topics discussed is necessary to understand their needs. As well, these communities and people in them can be quite diverse, and existing community detection methods have not been extended towards evaluating these heterogeneities. This has been limited as community detection methodologies have not focused on community detection based on semantic relations between textual features of the user-generated content. Thus here we develop an approach, NeuroCom, that optimally finds dense groups of users as communities in a latent space inferred by neural representation of published contents of users. By embedding of words and messages, we show that NeuroCom demonstrates improved clustering and identifies more nuanced discussion topics in contrast to other common unsupervised learning approaches

    Lean Thinking: Theory, Application and Dissemination

    Get PDF
    This book was written and compiled by the University of Huddersfield to share the learnings and experiences of seven years of Knowledge Transfer Partnership (KTP) and Economic and Social Research Council (ESRC) funded projects with the National Health Service (NHS). The focus of these projects was the implementation of Lean thinking and optimising strategic decision making processes. Each of these projects led to major local improvements and this book explains how they were achieved and compiles the lessons learnt. The book is split into three chapters; Lean Thinking Theory, Lean Thinking Applied and Lean Thinking Dissemination

    Big data analytics:Computational intelligence techniques and application areas

    Get PDF
    Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment
    • 

    corecore