21 research outputs found

    Geographic information extraction from texts

    Get PDF
    A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction

    LIPIcs, Volume 277, GIScience 2023, Complete Volume

    Get PDF
    LIPIcs, Volume 277, GIScience 2023, Complete Volum

    12th International Conference on Geographic Information Science: GIScience 2023, September 12–15, 2023, Leeds, UK

    Get PDF
    No abstract available

    Artificial Intelligence for Online Review Platforms - Data Understanding, Enhanced Approaches and Explanations in Recommender Systems and Aspect-based Sentiment Analysis

    Get PDF
    The epoch-making and ever faster technological progress provokes disruptive changes and poses pivotal challenges for individuals and organizations. In particular, artificial intelligence (AI) is a disruptive technology that offers tremendous potential for many fields such as information systems and electronic commerce. Therefore, this dissertation contributes to AI for online review platforms aiming at enabling the future for consumers, businesses and platforms by unveiling the potential of AI. To achieve this goal, the dissertation investigates six major research questions embedded in the triad of data understanding of online consumer reviews, enhanced approaches and explanations in recommender systems and aspect-based sentiment analysis

    Designing Data Spaces

    Get PDF
    This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty

    Exploiting general-purpose background knowledge for automated schema matching

    Full text link
    The schema matching task is an integral part of the data integration process. It is usually the first step in integrating data. Schema matching is typically very complex and time-consuming. It is, therefore, to the largest part, carried out by humans. One reason for the low amount of automation is the fact that schemas are often defined with deep background knowledge that is not itself present within the schemas. Overcoming the problem of missing background knowledge is a core challenge in automating the data integration process. In this dissertation, the task of matching semantic models, so-called ontologies, with the help of external background knowledge is investigated in-depth in Part I. Throughout this thesis, the focus lies on large, general-purpose resources since domain-specific resources are rarely available for most domains. Besides new knowledge resources, this thesis also explores new strategies to exploit such resources. A technical base for the development and comparison of matching systems is presented in Part II. The framework introduced here allows for simple and modularized matcher development (with background knowledge sources) and for extensive evaluations of matching systems. One of the largest structured sources for general-purpose background knowledge are knowledge graphs which have grown significantly in size in recent years. However, exploiting such graphs is not trivial. In Part III, knowledge graph em- beddings are explored, analyzed, and compared. Multiple improvements to existing approaches are presented. In Part IV, numerous concrete matching systems which exploit general-purpose background knowledge are presented. Furthermore, exploitation strategies and resources are analyzed and compared. This dissertation closes with a perspective on real-world applications

    Tracking the Temporal-Evolution of Supernova Bubbles in Numerical Simulations

    Get PDF
    The study of low-dimensional, noisy manifolds embedded in a higher dimensional space has been extremely useful in many applications, from the chemical analysis of multi-phase flows to simulations of galactic mergers. Building a probabilistic model of the manifolds has helped in describing their essential properties and how they vary in space. However, when the manifold is evolving through time, a joint spatio-temporal modelling is needed, in order to fully comprehend its nature. We propose a first-order Markovian process that propagates the spatial probabilistic model of a manifold at fixed time, to its adjacent temporal stages. The proposed methodology is demonstrated using a particle simulation of an interacting dwarf galaxy to describe the evolution of a cavity generated by a Supernov

    Urban Informatics

    Get PDF
    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

    Urban Informatics

    Get PDF
    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity
    corecore