1993
DOI: 10.1137/0222058
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Suffix Arrays: A New Method for On-Line String Searches

Abstract: A new and conceptually simple data structure, called a suffix array, for on-line string searches is intro

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Cited by 1,619 publications
(1,230 citation statements)
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References 24 publications
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“…With sophisticated techniques for proving upper and lower bounds on the complexity of searching V in lexicographic order, Andersson, Hagerup, Håstad and Petersson have proved in [1] that it requires Θ k log log n log log(4 + k log log n log n ) + k + log n time. This bound is worse than Θ(k + log n), obtained by searching V plus O(n) auxiliary locations (e.g., Manber and Myers [18]). Using permutations other than those resulting from sorting is a way to reach optimality: Franceschini and Grossi [10] have shown that for any set V of n vectors in lexicographic order, there exists a permutation of them allowing for Θ(k + log n) search time using O(1) auxiliary data locations.…”
Section: Introductionmentioning
confidence: 87%
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“…With sophisticated techniques for proving upper and lower bounds on the complexity of searching V in lexicographic order, Andersson, Hagerup, Håstad and Petersson have proved in [1] that it requires Θ k log log n log log(4 + k log log n log n ) + k + log n time. This bound is worse than Θ(k + log n), obtained by searching V plus O(n) auxiliary locations (e.g., Manber and Myers [18]). Using permutations other than those resulting from sorting is a way to reach optimality: Franceschini and Grossi [10] have shown that for any set V of n vectors in lexicographic order, there exists a permutation of them allowing for Θ(k + log n) search time using O(1) auxiliary data locations.…”
Section: Introductionmentioning
confidence: 87%
“…The pivots inside M B are kept searchable by a suitable blend of the techniques in [10,13,18], requiring to decode O(log n) heavy bits per inserted vector (which is fine since decoding takes O(1 + k/ log n) time). In particular, we logically divide each vector x into a concatenation of O(log m ) = O(log n) equally sized chunks.…”
Section: High-level Descriptionmentioning
confidence: 99%
“…A suffix array allows us to rapidly find a file (or files), containing any given substring. This is achieved with a binary search, and requires O(m + log 2 n) time on average, where m is the length of the substring (it is also possible to make this the worst case complexity, see [4]). The array can be constructed in time O(n log n), assuming atomic comparison of two tokens.…”
Section: Algorithm 1 Compare a File Against An Existing Collectionmentioning
confidence: 99%
“…We use suffix array as an index structure. A suffix array is a lexicographically sorted array of all suffixes of a given string [4]. The suffix array for the whole document collection is of size O(n).…”
Section: Algorithm 1 Compare a File Against An Existing Collectionmentioning
confidence: 99%
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