Efficient Storage and Retrieval by Content and Address of Static Files
Journal of the ACM (JACM)
Improved bounds for dictionary look-up with one error
Information Processing Letters
Succinct Representation of Balanced Parentheses and Static Trees
SIAM Journal on Computing
Efficient Minimal Perfect Hashing in Nearly Minimal Space
STACS '01 Proceedings of the 18th Annual Symposium on Theoretical Aspects of Computer Science
Approximate Dictionary Queries
CPM '96 Proceedings of the 7th Annual Symposium on Combinatorial Pattern Matching
Polynomial Hash Functions Are Reliable (Extended Abstract)
ICALP '92 Proceedings of the 19th International Colloquium on Automata, Languages and Programming
Efficient randomized pattern-matching algorithms
IBM Journal of Research and Development - Mathematics and computing
Note: A simple storage scheme for strings achieving entropy bounds
Theoretical Computer Science
Compressed Suffix Trees with Full Functionality
Theory of Computing Systems
Faster and Space-Optimal Edit Distance "1" Dictionary
CPM '09 Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching
The compressed permuterm index
ACM Transactions on Algorithms (TALG)
ACM Transactions on Algorithms (TALG)
Alphabet-independent compressed text indexing
ESA'11 Proceedings of the 19th European conference on Algorithms
Space-Efficient Preprocessing Schemes for Range Minimum Queries on Static Arrays
SIAM Journal on Computing
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In this paper we present different solutions for the problem of indexing a dictionary of strings in compressed space. Given a pattern P, the index has to report all the strings in the dictionary having edit distance at most one with P. Our first solution is able to solve queries in (almost optimal) O(|P|+occ) time where occ is the number of strings in the dictionary having edit distance at most one with P. The space complexity of this solution is bounded in terms of the k-th order entropy of the indexed dictionary. Our second solution further improves this space complexity at the cost of increasing the query time.