复合重复感知数据结构
Composite repetition-aware data structures
摘要：
在高度重复的字符串中，例如来自同一物种的基因组集合，重复的不同度量都在文本长度上呈亚线性增长，针对此类字符串的索引通常仅依赖于这些度量之一。我们描述了两个数据结构，其大小取决于一次重复的多个措施，并提供竞争力的时间之间的权衡，用于计数和报告所有的确切出现的模式，所采取的结构和空间。我们构造的关键组件是游程长度编码的BWT（RLBWT），它占用的空间与BWT游程的数量成比例：我们不是用后缀数组样本来扩充RLBWT，而是将其与来自LZ 77索引的数据结构（其占用与LZ 77因子的数量成比例的空间）以及与紧凑有向无环字图（CDAWG）相结合，其占用的空间与最大重复的延伸数成比例。CDAWG和RLBWT的组合也使一个新的表示后缀树，其大小再次取决于最大重复的扩展的数量，这是强大的，足以支持匹配统计和恒定空间遍历。
英文摘要：
In highly repetitive strings, like collections of genomes from the same species, distinct measures of repetition all grow sublinearly in the length of the text, and indexes targeted to such strings typically depend only on one of these measures. We describe two data structures whose size depends on multiple measures of repetition at once, and that provide competitive tradeoffs between the time for counting and reporting all the exact occurrences of a pattern, and the space taken by the structure. The key component of our constructions is the run-length encoded BWT (RLBWT), which takes space proportional to the number of BWT runs: rather than augmenting RLBWT with suffix array samples, we combine it with data structures from LZ77 indexes, which take space proportional to the number of LZ77 factors, and with the compact directed acyclic word graph (CDAWG), which takes space proportional to the number of extensions of maximal repeats. The combination of CDAWG and RLBWT enables also a new representation of the suffix tree, whose size depends again on the number of extensions of maximal repeats, and that is powerful enough to support matching statistics and constant-space traversal.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
