$\renewcommand{\Re}{\mathbb{R}}$Given a set $P$ of $n$ points in $\Re^d$, and a parameter $\varepsilon \in (0,1)$, we present a new construction of a directed graph $G$, of size $O(n/\varepsilon^d)$, such that $(1+\varepsilon)$-ANN queries can be answered by performing a greedy walk on $G$, repeatedly moving to a neighbor that is (significantly) better than the current point. To the best of our knowledge, this is the first construction of a linear size with no dependency on the spread of the point set. The resulting query time, is $O( \varepsilon^{-d} \log \Psi)$, where $\Psi$ is the spread of $P$. The new construction is surprisingly simple and should be practical.
翻译:给定d维实数空间$\\Re^d$中一个包含$n$个点的集合$P$,以及参数$\\varepsilon \\in (0,1)$,我们提出一种新的有向图$G$构造方法,其规模为$O(n/\\varepsilon^d)$。通过在图$G$上执行贪婪游走——反复移动到比当前点(显著)更优的邻居节点,即可回答$(1+\\varepsilon)$近似最近邻查询。据我们所知,这是首个规模与点集分布范围无关的线性构造方法。所得查询时间复杂度为$O( \\varepsilon^{-d} \\log \\Psi)$,其中$\\Psi$表示$P$的分布范围。该新构造方法具有出人意料的简洁性,并具备实际应用价值。