论文标题
通过量子随机步道解决Google搜索中的脱模词
Resolving degeneracies in Google search via quantum stochastic walks
论文作者
论文摘要
互联网是迄今为止发明的最有价值的技术之一。其中，Google是使用最广泛的搜索引擎。 Pagerank算法是Google Search的骨干，根据相关性和新颖性对网页进行排名。我们采用量子随机步行（QSW）来改善基于经典连续时间随机步行的经典Pagerank（CPR）算法。我们通过两个方案实施QSW：仅与不一致的不一致和脱颖而出。 Pagerank仅使用QSW与dephasing and Incroherence的不一致或QSW最好地分辨出通过CPR无法反应的脱糖性，并且与CPR相当的收敛时间（通常是最小值）。对于某些网络，与CPR相比，这两个QSW方案获得的收敛时间低于心肺复苏术，几乎无脱糖的排名。
The Internet is one of the most valuable technologies invented to date. Among them, Google is the most widely used search engine. The PageRank algorithm is the backbone of Google search, ranking web pages according to relevance and recency. We employ quantum stochastic walks (QSWs) to improve the classical PageRank (CPR) algorithm based on classical continuous time random walks. We implement QSW via two schemes: only incoherence and dephasing with incoherence. PageRank using QSW with only incoherence or QSW with dephasing and incoherence best resolves degeneracies that are unresolvable via CPR and with a convergence time comparable to that for CPR, which is generally the minimum. For some networks, the two QSW schemes obtain a convergence time lower than CPR and an almost degeneracy-free ranking compared to CPR.
