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Optimal Indexes for Sparse Bit Vectors

机译:稀疏位向量的最佳索引

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摘要

We consider the problem of supporting rank and select operations on a bit vector of length m with n 1-bits. The problem is considered in the succinct index model, where the bit vector is stored in "read-only" memory and an additional data structure, called the index is created during pre-processing to help answer the above queries. We give asymptotically optimal density-sensitive trade-offs, involving both m and n, that relate the size of the index to the number of accesses to the bit vector (and processing time) needed to answer the above queries. The results are particularly interesting for the case where n = o(m).
机译:我们考虑在具有n个1位的长度为m的位向量上支持秩和选择运算的问题。在简洁的索引模型中考虑了该问题,在该模型中,位向量存储在“只读”存储器中,并且在预处理期间创建了称为索引的附加数据结构以帮助回答上述查询。我们给出了涉及m和n的渐近最优密度敏感度折衷方案,这些折衷方案将索引的大小与回答上述查询所需的位向量访问次数(和处理时间)相关联。对于n = o(m)的情况,结果特别有趣。

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