稀少 发表于 2025-3-21 18:06:52
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Kelsey M. Lowe,Ian Moffatmetimes called “data mining” or “applied machine learning.” A new generation of knowledge discovery tools are beginning to address data that can be expressed as large graphs. Example applications include fraud detection in telecommunication networks and classifying Web pages based on hyperlink strucalabaster 发表于 2025-3-22 02:05:29
his is by design as the inherent objective of these methods is a globally uniform edge length or, more generally, accurate distance representation. The problem arises in graphs of high density or high conductance, and in the presence of high-degree vertices, all of which tend to pull vertices togeth溃烂 发表于 2025-3-22 07:42:42
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Neli Jordanova,Diana Jordanova,Maria Kostadinova-AvramovaHowever, there are many barriers in the way of someone wishing to make use of this technology. First, a potential user must know that the technology exists, which often means she must be well-versed in the terminology and literature of the graph drawing community. Then she must locate and install an约会 发表于 2025-3-22 19:22:20
http://reply.papertrans.cn/104/10311/1031089/1031089_7.pngevasive 发表于 2025-3-22 23:14:48
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Marc-Antoine Vella,Apostolos Sarris,Athos Agapiou,Vasiliki Lysandrourehension of the underlying data. With few exceptions, graph drawing algorithms typically optimize one such criterion, usually at the expense of others. We propose a layout approach, Graph Drawing via Gradient Descent, ., that can handle multiple readability criteria. . can optimize any criterion th