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• W3213818724 abstract "Suffix trees are a fundamental data structure in stringology, but their space usage, though linear, is an important problem in applications. We design and implement a new compressed suffix tree targeted to highly repetitive texts, such as large genomic collections of the same species. Our suffix tree builds on Block Trees, a recent Lempel-Ziv-bounded data structure that captures the repetitiveness of its input. We use Block Trees to compress the topology of the suffix tree, and augment the Block Tree nodes with data that speeds up suffix tree navigation. Our compressed suffix tree is slightly larger than previous repetition-aware suffix trees based on grammars, but outperforms them in time, often by orders of magnitude. The component that represents the tree topology achieves a speed comparable to that of general-purpose compressed trees, while using 2–10 times less space, and might be of independent interest." @default.
• W3213818724 created "2021-11-22" @default.
• W3213818724 creator A5046648612 @default.
• W3213818724 creator A5080743153 @default.
• W3213818724 date "2019-01-01" @default.
• W3213818724 modified "2023-09-27" @default.
• W3213818724 title "Faster Repetition-Aware Compressed Suffix Trees Based on Block Trees" @default.
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• W3213818724 doi "https://doi.org/10.1007/978-3-030-32686-9_31" @default.
• W3213818724 hasPublicationYear "2019" @default.
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