Enhanced Graph Pattern Matching
<|reference_start|>Enhanced Graph Pattern Matching: Pattern matching queries on strings can be solved in linear time by Knuth-Morris-Pratt (KMP) algorithm. In 1973, Weiner introduced the suffix tree of a string [FOCS 1973] and showed that the seemingly more difficult problem of computing matching statistics can also be solved in liner time. Pattern matching queries on graphs are inherently more difficult: under the Orthogonal Vector hypothesis, the graph pattern matching problem cannot be solved in subquadratic time [TALG 2023]. The complexity of graph pattern matching can be parameterized by the topological complexity of the considered graph, which is captured by a parameter $ p $ [JACM 2023].   In this paper, we show that, as in the string setting, computing matching statistics on graph is as difficult as solving standard pattern matching queries. To this end, we introduce a notion of longest common prefix (LCP) array for arbitrary graphs.<|reference_end|>
@article{cotumaccio2024enhanced,
    title={Enhanced Graph Pattern Matching},
    author={Nicola Cotumaccio},
    journal={arXiv preprint arXiv:2402.16205},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.16205},
    primaryClass={cs.DS}
}