Combinatorial Methods for String Processing
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Strings, or sequences, are the most fundamental form of digital data. Due to recent developments in sensor network technologies and semi-automated machine-to- machine (M2M) communications, sequential data have been increasing more rapidly than ever. It is o5en the case that such semi-automatically generated sequential data contain abundant repetitive structures. Thus, understanding, revealing, and utilizing combinatorial objects that reside in strings are of great significance in designing efficient string processing algorithms and data structures. Typical topics of interests include (but are ...
Strings, or sequences, are the most fundamental form of digital data. Due to recent developments in sensor network technologies and semi-automated machine-to- machine (M2M) communications, sequential data have been increasing more rapidly than ever. It is o5en the case that such semi-automatically generated sequential data contain abundant repetitive structures. Thus, understanding, revealing, and utilizing combinatorial objects that reside in strings are of great significance in designing efficient string processing algorithms and data structures. Typical topics of interests include (but are not limited to): - Combinatorial string problems and solutions; - Pattern matching algorithms; - Applied combinatorics on words; - Text compression; - Data structures for strings, labeled trees, and compressed text. This Special Issue contains five peer-reviewed papers.
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