6533b827fe1ef96bd1285b36
RESEARCH PRODUCT
Linear-size suffix tries
Roberto GrossiMaxime CrochemoreChiara EpifanioFilippo Mignosisubject
Compressed suffix arrayGeneral Computer ScienceSuffix tree[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Generalized suffix tree0102 computer and information sciences02 engineering and technologyData_CODINGANDINFORMATIONTHEORYText indexing01 natural sciencesY-fast trielaw.inventionLongest common substring problemTheoretical Computer ScienceCombinatoricsSuffix treelawFactor and suffix automata0202 electrical engineering electronic engineering information engineeringData_FILESArithmeticFactor and suffix automata; Pattern matching; Suffix tree; Text indexing; Theoretical Computer Science; Computer Science (all)Pattern matchingMathematicsSettore INF/01 - InformaticaX-fast trieComputer Science (all)LCP array010201 computation theory & mathematics020201 artificial intelligence & image processingFM-indexdescription
Suffix trees are highly regarded data structures for text indexing and string algorithms [MCreight 76, Weiner 73]. For any given string w of length n = | w | , a suffix tree for w takes O ( n ) nodes and links. It is often presented as a compacted version of a suffix trie for w, where the latter is the trie (or digital search tree) built on the suffixes of w. Here the compaction process replaces each maximal chain of unary nodes with a single arc. For this, the suffix tree requires that the labels of its arcs are substrings encoded as pointers to w (or equivalent information). On the contrary, the arcs of the suffix trie are labeled by single symbols but there can be Θ ( n 2 ) nodes and links for suffix tries in the worst case because of their unary nodes. It is an interesting question if the suffix trie can be stored using O ( n ) nodes. We present the linear-size suffix trie, which guarantees O ( n ) nodes. We use a new technique for reducing the number of unary nodes to O ( n ) , that stems from some results on antidictionaries. For instance, by using the linear-size suffix trie, we are able to check whether a pattern p of length m = | p | occurs in w in O ( m log | Σ | ) time and we can find the longest common substring of two strings w 1 and w 2 in O ( ( | w 1 | + | w 2 | ) log | Σ | ) time for an alphabet Σ.
year | journal | country | edition | language |
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2016-01-01 |