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Abstract

In der Gesetzgebungsdebatte zur Verabschiedung des Zweiten Gesetzes zur Regelung des Urheberrechts in der Informationsgesellschaft wurde bereits im Jahre 2006 ein Dritter Korb speziell für die Belange von Bildung und Wissenschaft in Aussicht gestellt. Der Bundesrat hatte ein bildungs- und wissenschaftsfreundlicheres Urheberrecht bzw. ein dezidiertes WissenschaftsUrheberrecht gefordert. Die Allianz der deutschen Wissenschaftsorganisationen hält es für dringend erforderlich, in der laufenden Legislaturperiode die Arbeit an diesen für die Wissenschaft immens wichtigen ergänzenden Regelungen zu einem Abschluss zu bringen. Sie unterbreitet deshalb dem Gesetzgeber konkrete Vorschläge für u.a. ein Zweitveröffentlichungsrecht, für verwaiste Werke und für eine allgemeine Wissenschaftsschranke.

Source

Zeitschrift für Bibliothekswesen und Bibliographie. 57(2010) H.5, S.245-252

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Abstract

Large amounts of medical visual data are produced in hospitals daily and made available continuously via publications in the scientific literature, representing the medical knowledge. However, it is not always easy to find the desired information and in clinical routine the time to fulfil an information need is often very limited. Information retrieval systems are a useful tool to provide access to these documents/images in the biomedical literature related to information needs of medical professionals. Shangri-La is a medical retrieval system that can potentially help clinicians to make decisions on difficult cases. It retrieves articles from the biomedical literature when querying a case description and attached images. The system is based on a multimodal retrieval approach with a focus on the integration of visual information connected to text. The approach includes a query-adaptive multimodal fusion criterion that analyses if visual features are suitable to be fused with text for the retrieval. Furthermore, image modality information is integrated in the retrieval step. The approach is evaluated using the ImageCLEFmed 2013 medical retrieval benchmark and can thus be compared to other approaches. Results show that the final approach outperforms the best multimodal approach submitted to ImageCLEFmed 2013.

Footnote

Beitrag in einem Special issue on biomedical information retrieval.