One-time approximate mode matching method with local-integral constraints

Abstract

Provided is a one-time approximate mode matching method with local-integral constraints, relating to the technical field of digital processing. A network tree structure is used to solve a one-time approximate pattern matching problem under (Delta, Gamma)-distance. Firstly, a sequence S, a mode P, a local threshold Delta and overall threshold Gamma are read to create a network tree according to aninput condition. Then, starting from a last node of a leaf layer, according to a rightmost parent strategy and a greedy search parent strategy, the occurrence of the larger number of remaining occurrences is selected and the process is iterated until the first node of the leaf layer to find a maximum result set. Finally, all occurrences of pattern P in sequence S are outputted. The present invention overcomes a one-time approximation pattern matching problem with local-integral constraints in the prior art. Generality, accuracy, and flexibility are integrated and the drawback of a solution setis not redundant.

Description

technical field [0001] The technical solution of the invention relates to the technical field of electrical digital data processing, in particular to a one-time approximate pattern matching method with local-total constraints. Background technique [0002] With the continuous development of Internet technology, the scale of data is increasing rapidly. How to use data mining technology to find valuable information from a large amount of data has become a research hotspot. Frequent pattern mining refers to finding frequent patterns from a large amount of data. , its main task is pattern matching, because frequent pattern mining usually needs to calculate the support of a pattern, and the essence of support calculation is the pattern matching problem, therefore, pattern matching is the basis and core of frequent pattern mining, with the development of science and technology With each passing day, pattern matching technology has been widely used in various fields, not only for s...

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Problems solved by technology

[0027] Pattern matching problems generally require generality, accuracy, and flexibility, and the solution set must be non-redundant, which can reduce the difficulty of data analysis and processing, but the existing related technologies are difficult to meet these conditions at the same time, for example, Wu et al. The paper "A Heuristic Method for Solving the MPMGOOC Problem, Journal of Computers." Based on the network tree structure, the pattern matching with gap constraints and one-time conditions is studied. This paper proposes a heuristic method, that is, through the most The right parent strategy and the greedy search parent strategy to find the optimal occurrence have improved the quality of the solution compared with other methods, and are of reference value for solving other complex problems. However, this method studies exact pattern matching and cannot deal with data noise. Not general; the document "SAIL-APPROX: An Efficient On-Line Algorithm for Approximate Pattern Matching with Wildcards and Length Constraints, IEEE." Approximate pattern matching, and proved the correctness and effectiveness of the proposed method, but this literature studies the approximate pattern matching under Hamming distance, Hamming distance does not consider the local constraints between sequences, which will lead to huge Bias, not accurate; Tang et al. published the document "Approximate pattern matching with gap constraints, Journal of Information Science." studied approximate pattern matching with gap constraints, and proposed an efficient solution method based on a single net tree, Compared with exact pattern matching, more valuable information can be found in many fields, but this literature studies approximate pattern matching without special conditions, which allows characters at any position in the sequence to be used multiple times, resulting in patterns in The number of occurrences in the sequence increases exponentially with the length of the pattern, which increases the complexity of the problem; the literature published by Liu et al. "An improved BM pattern matching method, computer engineering." On the basis of the BM method, By judging whether there are continuous characters in the pattern, and then changing the comparison order of the pattern, the matching efficiency of the BM method is improved. However, this document matches continuous characters, without gap constraints, and lacks flexibility.

[0028] In short, for the one-shot approximate pattern matching problem with local-global constraints, the existing one-shot approximate pattern matching technology is difficult to take into account the generality, accuracy and flexibility of the solution, and the solution set must be non-redundant. A good way to solve this kind of problem appears

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