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Titlebook: Analysis and Visualization of Citation Networks; Dangzhi Zhao,Andreas Strotmann Book 2015 Springer Nature Switzerland AG 2015

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樓主: ACRO
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發(fā)表于 2025-3-25 07:07:53 | 只看該作者
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發(fā)表于 2025-3-25 20:50:01 | 只看該作者
An Improvement of Dissimilarity-Based Classifications Using SIFT Algorithmissimilarity measure among the objects. In this paper, we study a new way of measuring the dissimilarity between two object images using a SIFT (Scale Invariant Feature Transformation) algorithm [5], which transforms image data into scale-invariant coordinates relative to local features based on the
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發(fā)表于 2025-3-26 00:46:43 | 只看該作者
Value Creation, Capture, and Allocation,and vertical value chains as four significant value drivers. It also proposes various initiatives to combine these drivers with network integration strategies to create synergy effects in the value creation process. Value creation, by definition, is related to how much target customers subjectively
27#
發(fā)表于 2025-3-26 04:56:19 | 只看該作者
Conference proceedings 2004 e?ort of number theorists from around the world. There were four invited talks at ANTS VI, by Dan Bernstein of the Univ- sity of Illinois at Chicago, Kiran Kedlaya of MIT, Alice Silverberg of Ohio State University, and Mark Watkins of Pennsylvania State University. Thirty cont- buted talks were pre
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發(fā)表于 2025-3-26 12:13:04 | 只看該作者
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發(fā)表于 2025-3-26 14:20:34 | 只看該作者
Conference proceedings 2011rganized algorithms applied to complex networks, as well as many applications of complex networks in biology, image analysis, software development, traffic congestion, language and speech, sensor networks, and synchronization.
30#
發(fā)表于 2025-3-26 18:57:23 | 只看該作者
Meeting and Joining Theme Models in Vector Spaces for Information Retrievales while join builds a plane from two lines. Since an operator applies to a pair of themes and results in another theme operators and theme models replace the traditional retrieval models. The experimental results show that this approach can compete with – it can retrieve relevant documents missed by – traditional retrieval models.
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