We introduce a data structure, the Bundled Suffix Tree (BUST), that is a generalization of a Suffix Tree (ST). To build a BuST we use an alphabet Σ together with a non-transitive relation ≈ among its letters. Following the path of a substring β within a BUST, constructed over a text α of length n, not only the positions of the exact occurrences of β in α are found (as in a ST), but also the positions of all the substrings α1, α2, α3 ⋯ that are related with β via the relation ≈ among the characters of ∑, for example strings at a certain “distance” from β. A BuST contains O(n 1+δ) additional nodes (δ < 1) in probability, and is constructed in O(n 1+δ) steps. In the worst case it contains O(n 2) nodes. Please use the following format when citing this chapter: Bortolussi, L., Fabris, F., Policriti, A., 2006, in International Federation for Information Processing, Volume 209, Fourth IFIP International Conference on Theoretical Computer Science-TCS 2006, eds. Navarro, G., Bertossi, L., Kohayakwa, Y., (Boston: Springer). pp. 91–102.
BuST-Bundled Suffix Trees
BORTOLUSSI, LUCA;FABRIS, FRANCESCO;
2006-01-01
Abstract
We introduce a data structure, the Bundled Suffix Tree (BUST), that is a generalization of a Suffix Tree (ST). To build a BuST we use an alphabet Σ together with a non-transitive relation ≈ among its letters. Following the path of a substring β within a BUST, constructed over a text α of length n, not only the positions of the exact occurrences of β in α are found (as in a ST), but also the positions of all the substrings α1, α2, α3 ⋯ that are related with β via the relation ≈ among the characters of ∑, for example strings at a certain “distance” from β. A BuST contains O(n 1+δ) additional nodes (δ < 1) in probability, and is constructed in O(n 1+δ) steps. In the worst case it contains O(n 2) nodes. Please use the following format when citing this chapter: Bortolussi, L., Fabris, F., Policriti, A., 2006, in International Federation for Information Processing, Volume 209, Fourth IFIP International Conference on Theoretical Computer Science-TCS 2006, eds. Navarro, G., Bertossi, L., Kohayakwa, Y., (Boston: Springer). pp. 91–102.Pubblicazioni consigliate
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