Given a dynamic set $\mathcal{K}$ of k strings of total length n whose characters are drawn from an alphabet of size σ, a keyword dictionary is a data structure built on $\mathcal{K}$ that provides lookup, prefix search, and update operations on $\mathcal{K}$. Under the assumption that $\alpha =w/\lg \sigma$ characters fit into a single machine word of w bits, we propose a keyword dictionary that represents $\mathcal{K}$ in either $n\lg \sigma +\mathrm{\Theta }(k\lg n)$ or $|T|\lg \sigma +\mathrm{\Theta }(kw)$ bits of space, where $|T|$ is the number of nodes of a trie representing $\mathcal{K}$. It supports all operations in $\mathcal{O}(m/\alpha +\lg \alpha )$ expected time on an input string of length m in the word RAM model. An evaluation of our implementation highlights the practical usefulness of the proposed data structure, especially for prefix searches — one of the most essential keyword dictionary operations.

给定一个动态集$\mathcal{ķ}$k个总长度为n的字符串，其字符来自大小为σ的字母表，关键字字典是建立在$\mathcal{ķ}$提供查找、前缀搜索和更新操作$\mathcal{ķ}$. 在假设下$\alpha =w/\lg \sigma$字符适合w位的单个机器词，我们提出了一个关键字字典，表示$\mathcal{ķ}$在任一$n\lg \sigma +\mathrm{\theta }(ķ\lg n)$或者$|吨|\lg \sigma +\mathrm{\theta }(ķw)$位空间，在哪里$|吨|$是表示树的节点数$\mathcal{ķ}$. 它支持所有操作$\mathcal{○}(米/\alpha +\lg \alpha )$字 RAM 模型中长度为m的输入字符串的预期时间。对我们实现的评估强调了所提出的数据结构的实际用途，特别是对于前缀搜索——最重要的关键字字典操作之一。