# Various improvements to text fingerprinting

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Various improvements to text fingerprinting**

Let s = s 1

s n be a text or sequence on a finite alphabet \Sigma of size \sigma. A fingerprint in s is the set of distinct characters appearing in one of its substrings. The problem considered here is to compute the set {\cal F} of all fingerprints of all substrings of s in order to answer efficiently certain questions on this set. A substring s i

s j is a maximal location for a fingerprint f in F denoted by if the alphabet of s i

s j is f and s {i-1}, s {j+1}, if defined, are not in f. The set of maximal locations ins is {\cal L} it is easy to see that |{\cal L}| \leq n \sigma. Two maximal locations and such that s i

s j = s k

s l are named {\em copies}, and the quotient set of {\cal L} according to the copy relation is denoted by {\cal L} C. We present new exact and approximate efficient algorithms and data structures for the following three problems: 1 to compute {\cal F}; 2 given f as a set of distinct characters in \Sigma, to answer if f represents a fingerprint in {\cal F}; 3 given f, to find all maximal locations of f in s.

Author: **Djamal Belazzougui; Roman Kolpakov; Mathieu Raffinot**

Source: https://archive.org/