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End date: 2019 × Start date: 2019 × Start date: 1984 × DDC: 004 × Type: Text × WGL Institute: TIB ×

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Now showing 1 - 3 of 3
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    The quest for research information
    (Amsterdam : Elsevier, 2014) Blümel, Ina; Dietze, Stefan; Heller, Lambert; Jäschke, Robert; Mehlberg, Martin
    Research information, i.e., data about research projects, organisations, researchers or research outputs such as publications or patents, is spread across the web, usually residing in institutional and personal web pages or in semi-open databases and information systems. While there exists a wealth of unstructured information, structured data is limited and often exposed following proprietary or less-established schemas and interfaces. Therefore, a holistic and consistent view on research information across organisational and national boundaries is not feasible. On the other hand, web crawling and information extraction techniques have matured throughout the last decade, allowing for automated approaches of harvesting, extracting and consolidating research information into a more coherent knowledge graph. In this work, we give an overview of the current state of the art in research information sharing on the web and present initial ideas towards a more holistic approach for boot-strapping research information from available web sources.
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    Efficient retrieval of 3D building models using embeddings of attributed subgraphs
    (Institut für Informatik II, Universität Bonn, 2011) Wessel, R.; Ochmann, S.; Vock, R.; Blümel, Ina; Klein, R.
    We present a novel method for retrieval and classification of 3D building models that is tailored to the specific requirements of architects. In contrast to common approaches our algorithm relies on the interior spatial arrangement of rooms instead of exterior geometric shape. We first represent the internal topological building structure by a Room Connectivity Graph (RCG). Each room is characterized by a node. Connections between rooms like e.g. doors are represented by edges. Nodes and edges are additionally assigned attributes reflecting room and edge properties like e.g area or window size. To enable fast and efficient retrieval and classification with RCGs, we transform the structured graph representation into a vector-based one. We first decompose the RCG into a set of subgraphs. For each subgraph, we compute the similarity to a set of codebook graphs. Aggregating all similarity values finally provides us with a single vector for each RCG which enables fast retrieval and classification. For evaluation, we introduce a classification scheme that was carefully developed following common guidelines in architecture.We finally provide comprehensive experiments showing that the introduced subgraph embeddings yield superior performance compared to state-of-the-art graph retrieval approaches.
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    RADAR-Team stellt Testsystem auf zweitem Projekt-Workshop in Frankfurt vor
    (Karlsruhe : KIT, 2015) Potthoff, Jan; Razum, Matthias; Kraft, Angelina
    Im Rahmen des Projekts "Research Data Repository" (RADAR) wurde am 23. Juni 2015 auf dem zweiten Projekt-Workshop der aktuelle Stand des Testsystems, das zur Archivierung und Publikation von Forschungsdaten genutzt werden kann, vorgestellt. Außerdem wurden weitere Anforderungen an das System und allgemeine Fragen des Forschungsdatenmanagements mit den Workshop-Teilnehmern diskutiert.