Detecting leftmost maximal periodicities
Discrete Applied Mathematics - Combinatorics and complexity
Suffix arrays: a new method for on-line string searches
SIAM Journal on Computing
A theory of parameterized pattern matching: algorithms and applications
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Alphabet dependence in parameterized matching
Information Processing Letters
Multiple matching of parameterized patterns
Theoretical Computer Science
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Parameterized pattern matching by Boyer-Moore-type algorithms
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Efficient string matching: an aid to bibliographic search
Communications of the ACM
Linear-Time Longest-Common-Prefix Computation in Suffix Arrays and Its Applications
CPM '01 Proceedings of the 12th Annual Symposium on Combinatorial Pattern Matching
Faster algorithms for the construction of parameterized suffix trees
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Faster Suffix Tree Construction with Missing Suffix Links
SIAM Journal on Computing
Finding Clones with Dup: Analysis of an Experiment
IEEE Transactions on Software Engineering
Computing Longest Previous Factor in linear time and applications
Information Processing Letters
A Simple Algorithm for Computing the Lempel Ziv Factorization
DCC '08 Proceedings of the Data Compression Conference
The Burrows-Wheeler Transform: Data Compression, Suffix Arrays, and Pattern Matching
The Burrows-Wheeler Transform: Data Compression, Suffix Arrays, and Pattern Matching
Space-Time Tradeoffs for Longest-Common-Prefix Array Computation
ISAAC '08 Proceedings of the 19th International Symposium on Algorithms and Computation
Permuted Longest-Common-Prefix Array
CPM '09 Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching
Combinatorial Algorithms
Efficient Algorithms for Two Extensions of LPF Table: The Power of Suffix Arrays
SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
Information Processing Letters
IEEE Spectrum
On-line construction of parameterized suffix trees for large alphabets
Information Processing Letters
Computing Longest Previous non-overlapping Factors
Information Processing Letters
Parameterized longest previous factor
IWOCA'11 Proceedings of the 22nd international conference on Combinatorial Algorithms
p-Suffix sorting as arithmetic coding
IWOCA'11 Proceedings of the 22nd international conference on Combinatorial Algorithms
A universal algorithm for sequential data compression
IEEE Transactions on Information Theory
Variations of the parameterized longest previous factor
Journal of Discrete Algorithms
p-Suffix sorting as arithmetic coding
Journal of Discrete Algorithms
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Journal of Discrete Algorithms
| Hi-index | 5.23 |
Given a string W, the longest previous factor (LPF) problem is to determine the maximum length of a previously occurring factor for each suffix occurring in W. The LPF problem is defined for traditional strings exclusively from the constant alphabet @S. A parameterized string (p-string) is a string composed of symbols from a constant alphabet @S and a parameter alphabet @P. We formulate the LPF problem in terms of p-strings by defining the parameterized longest previous factor (pLPF) problem. Subsequently, we present an expected linear time solution to construct the parameterized longest previous factor (pLPF) array. Given our pLPF solution, we show how to construct the pLCP (parameterized longest common prefix) array with the same general algorithm. We exploit the properties of the pLPF data structure to also construct the standard LPF (longest previous factor) and LCP (longest common prefix) arrays all in linear time. Further, we provide insight into the practicality of our construction algorithms.