Abstract
Some recognition problems are either too complex or too ambiguous to be expressed as a simple pattern matching problem using a sequence or regular expression pattern. In these cases, a richer environment is needed to describe the “patterns” and recognition techniques used to perform the recognition. Some researchers have turned to artificial-intelligence techniques and multistep matching approaches for the problems of gene recognition [5], [7], [18], protein structure recognition [13], and on-line character recognition [6]. This paper presents a class of problems which involve finding matches to “patterns of patterns,” orsuper- patterns, given solutions to the lower-level patterns. The expressiveness of this problem class rivals that of traditional artificial-intelligence characterizations, and yet polynomial-time algorithms are described for each problem in the class.
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Communicated by E. W. Myers.
This work was supported in part by the National Institute of Health under Grant ROI LM04960 and by the Aspen Center for Physics.
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Knight, J.R., Myers, E.W. Super-pattern matching. Algorithmica 13, 211–243 (1995). https://doi.org/10.1007/BF01188587
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DOI: https://doi.org/10.1007/BF01188587