论文标题
非局部Pagerank
Nonlocal PageRank
论文作者
论文摘要
在这项工作中，我们介绍并研究了Pagerank的非本地版本。在我们的方法中，随机沃克使用较长的游览探索图，而不是在相邻节点之间移动。结果，在它们之间考虑了\ textIt {远程相互作用}的相应排名并不显示频谱排名的典型浓度现象，这些现象仅考虑了局部相互作用。我们表明，使用我们的建议获得的排名的预测价值在不同的现实世界问题上得到了很大改善。
In this work we introduce and study a nonlocal version of the PageRank. In our approach, the random walker explores the graph using longer excursions than just moving between neighboring nodes. As a result, the corresponding ranking of the nodes, which takes into account a \textit{long-range interaction} between them, does not exhibit concentration phenomena typical of spectral rankings which take into account just local interactions. We show that the predictive value of the rankings obtained using our proposals is considerably improved on different real world problems.
