132,181 research outputs found

    Lieutenant Colonel D. L. Stricker

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    Lieutenant Colonel D.L. Stricker, 2nd Delaware Volunteer

    Lieutenant Colonel D. L. Stricker

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    Lieutenant Colonel D.L. Stricker, 2nd Delaware Volunteer

    Berechnete Unbestimmtheit: Paradoxien der Freiheit im digitalen Zeitalter

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    Verständig D, Stricker J. Berechnete Unbestimmtheit: Paradoxien der Freiheit im digitalen Zeitalter. In: Verständig D, Kast C, Stricker J, Nürnberger A, eds. Algorithmen und Autonomie: Interdisziplinäre Perspektiven auf das Verhältnis von Selbstbestimmung und Datenpraktiken. Leverkusen: Barbara Budrich; 2022: 25-47

    Alana Stricker, Piano

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    Sonata in E major K. 380; Sonata in G Major L. 180 / Domenico Scarlatti; Sonata No. 2 in D Minor / Sergei Prokofiev; Scherzo No. 3 in C Sharp Minor / Frédéric Chopi

    Algorithmen und Autonomie - Ein Problemaufriss

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    Verständig D, Kast C, Stricker J, Nürnberger A. Algorithmen und Autonomie - Ein Problemaufriss. In: Verständig D, Kast C, Stricker J, Nürnberger A, eds. Algorithmen und Autonomie. Interdisziplinäre Perspektiven auf das Verhältnis von Selbstbestimmung und Datenpraktiken. Leverkusen: Barbara Budrich; 2022: 7-24

    Ein Modellprojekt zu Robotern in der Schule

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    Verständig D, Stricker J. Ein Modellprojekt zu Robotern in der Schule. On: Lernen in der digitalen Welt . 2021;2021(5):18-19

    MeSH term explosion and author rank improve expert recommendations

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    Information overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
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