Managing and mining large graphs
作者： Christos Faloutsos , U. Kang
关键词: Graph kernel 、 Molecule mining 、 Graph 、 Biological network 、 Computer science 、 Algorithm 、 Scalability 、 Theoretical computer science
摘要: Graphs are everywhere: social networks, the World Wide Web, biological and many more. The sizes of graphs growing at unprecedented rate, spanning millions billions nodes edges. What patterns in large graphs, Giga, Tera, heading toward Peta bytes? best tools, how can they help us solve graph mining problems? How do we scale up algorithms for handling with edges? These exactly goals this tutorial. We start real-world static, weighted, dynamic graphs. Then describe important tools mining, including singular value decomposition, Hadoop. Finally, conclude design implementation scalable on Hadoop.This tutorial is complementary to related "Managing Mining Large Graphs: Systems Implementations".
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sci-hub.se 参考文章(18)
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