Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
An efficient algorithm for dynamic text indexing
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
A Space-Economical Suffix Tree Construction Algorithm
Journal of the ACM (JACM)
A fast string searching algorithm
Communications of the ACM
Perfect Hashing for Strings: Formalization and Algorithms
CPM '96 Proceedings of the 7th Annual Symposium on Combinatorial Pattern Matching
Efficient approximate and dynamic matching of patterns using a labeling paradigm
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Dictionary matching and indexing with errors and don't cares
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Faster index for property matching
Information Processing Letters
Property matching and weighted matching
Theoretical Computer Science
Linear pattern matching algorithms
SWAT '73 Proceedings of the 14th Annual Symposium on Switching and Automata Theory (swat 1973)
Errata for “Faster index for property matching”
Information Processing Letters
Simple linear work suffix array construction
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
Compressed property suffix trees
Information and Computation
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Recently there has been much interest in the Property Indexing Problem ([1],[7],[8]), where one is interested to preprocess a text T of size n over alphabet Σ (which we assume is of constant size), and a set of intervals π over the text positions, such that give a query pattern P of size m we can report all of the occurrences of P in T which are completely contained within some interval from π. This type of matching is extremely helpful in scenarios in molecular biology where it has long been a practice to consider special areas in the genome by their structure. The work done so far has focused on the static version of this problem where the intervals are given a-priori and never changed. This paper is the first to focus on several dynamic settings of π including an incremental version where new intervals are inserted into π, decremental version where intervals are deleted from &pi, fully dynamic version where intervals may be inserted or deleted to or from π, or batched insertions where a set of intervals is inserted into π. In particular, the batched version provides us with a new (optimal) algorithm for the static case.