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Titlebook: Innovation Networks; New Approaches in Mo Andreas Pyka,Andrea Scharnhorst Book 2009 Springer-Verlag Berlin Heidelberg 2009 Evolution.Innova

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樓主: Limbic-System
31#
發(fā)表于 2025-3-27 00:42:29 | 只看該作者
32#
發(fā)表于 2025-3-27 03:12:22 | 只看該作者
Death of Distance in Science? A Gravity Approach to Research Collaborationeasingly depends on a region’s position in global networks rather than its specific local characteristics such as institutions, endowments and amenities (‘space of flows’ versus the ‘space of places’).
33#
發(fā)表于 2025-3-27 07:46:44 | 只看該作者
34#
發(fā)表于 2025-3-27 10:05:56 | 只看該作者
35#
發(fā)表于 2025-3-27 15:39:37 | 只看該作者
36#
發(fā)表于 2025-3-27 20:26:53 | 只看該作者
learns user community by using community detection method and message clustering by using short texts clustering algorithm from social contextual information on the basis of homophily assumption, respectively. Then CBRMF incorporates the impacts of homophily characteristics on users and messages as
37#
發(fā)表于 2025-3-27 22:23:31 | 只看該作者
Pier Paolo Saviotti, to alleviate the staleness problem, SGC updates model weight with the accumulation of delayed gradients at local, called local update technique. The experiments over the sparse high-dimensional models and deep neural networks indicate that SGC can compress 99.99% gradients for every iteration with
38#
發(fā)表于 2025-3-28 04:44:39 | 只看該作者
Koen Frenken,Jarno Hoekman,Suzanne Kok,Roderik Ponds,Frank van Oort,Joep van Vlietrtional to the their degrees, depending on how repeatedly the area has been visited. Experimental results show that our solver significantly outperforms state-of-the-art MinDS solvers. Also we conducted several experiments to show the individual impacts of our novelties.
39#
發(fā)表于 2025-3-28 07:59:33 | 只看該作者
Frank Beckenbach,Ramón Briegel,Maria Daskalakis logging. We conduct trace-driven experiments on the TPC-C benchmark to measure the performance of our proposal. The results show that LFLogging achieves up to 4~5X improvement in system throughput than existing approaches including WAL and PCMLogging.
40#
發(fā)表于 2025-3-28 11:00:59 | 只看該作者
Andreas Pyka,Nigel Gilbert,Petra Ahrweiler represented as vector space model (VSM) using TF-IDF after words segmentation. To improve performance, we construct a set of judicial stop words. Besides, as TF-IDF generates a high dimensional feature vector, which leads to an extremely high time complexity, we utilize three dimensional reduction
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