Theoretical Computer Science
Text algorithms
Pattern matching algorithms
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Approximate String-Matching over Suffix Trees
CPM '93 Proceedings of the 4th Annual Symposium on Combinatorial Pattern Matching
CPM '97 Proceedings of the 8th Annual Symposium on Combinatorial Pattern Matching
ICALP '01 Proceedings of the 28th International Colloquium on Automata, Languages and Programming,
Reliable Detection of Episodes in Event Sequences
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Episode directed acyclic subsequence graph
Nordic Journal of Computing
Reliable detection of episodes in event sequences
Knowledge and Information Systems
An inexact-suffix-tree-based algorithm for detecting extensible patterns
Theoretical Computer Science - Pattern discovery in the post genome
Journal of the ACM (JACM)
Algebraic aspects of some Riordan arrays related to binary words avoiding a pattern
Theoretical Computer Science
Bridging lossy and lossless compression by motif pattern discovery
General Theory of Information Transfer and Combinatorics
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Given two strings X=a1...an and P=b1...bm over an alphabet , the problem of testing whether P occurs as a subsequence of X is trivially solved in linear time. It is also known that a simple O (n log ||) time preprocessing of X makes it easy to decide subsequently, for any P and in at most |P| log || character comparisons, whether P is a subsequence of X. These problems become more complicated if one asks instead whether P occurs as a subsequence of some substring Y of X of bounded length. This paper presents an automaton built on the textstring X and capable of identifying all distinct minimal substrings Y of X having P as a subsequence. By a substring Y being minimal with respect to P, it is meant that P is not a subsequence of any proper substring of Y. For every minimal substring Y, the automaton recognizes the occurrence of P having the lexicographically smallest sequence of symbol positions in Y. It is not difficult to realize such an automaton in time and space O (n2) for a text of n characters. One result of this paper consists of bringing those bounds down to linear or O (n log n), respectively, depending on whether the alphabet is bounded or of arbitrary size, thereby matching the corresponding complexities of automata constructions for offline exact string searching. Having built the automaton, the search for all lexicographically earliest occurrences of P in X is carried out in time O (i=1mroccii) or O (n+i=1mroccii log n), depending on whether the alphabet is fixed or arbitrary, where rocci is the number of distinct minimal substrings of X having b1...bi as a subsequence (note that each such substring may occur many times in X but is counted only once in the bound). All log factors appearing in the above bounds can be further reduced to log log by resorting to known integer-handling data structures.