Introduction to algorithms
The string B-tree: a new data structure for string search in external memory and its applications
Journal of the ACM (JACM)
Efficient suffix trees on secondary storage
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Cache-oblivious string dictionaries
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Cache-oblivious string B-trees
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On searching compressed string collections cache-obliviously
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Algorithms and Data Structures for External Memory
Algorithms and Data Structures for External Memory
Data structures: time, I/Os, entropy, joules!
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part II
Fast prefix search in little space, with applications
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Obtaining provably good performance from suffix trees in secondary storage
CPM'06 Proceedings of the 17th Annual conference on Combinatorial Pattern Matching
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The weak-prefix search problem asks for the strings in a dictionary S that are prefixed by a pattern P[1, p], if any, otherwise it admits any answer. Strings in S have average length l, are n in number, and are given in advance to be preprocessed, whereas pattern P is provided on-line. In this paper we solve this problem in the cache-oblivious model by using the optimal O(n log l) bits of space and O(p/B + logB n) I/Os. The searching algorithm is of Monte-Carlo type, so its answer is correct with high probability. We also extend our algorithmic scheme to the case in which a probability distribution over the queried prefixes is known, and eventually address the deterministic case too.