Approximate String Matching by Fuzzy Automata (original) (raw)

Adjusting fuzzy automata for string similarity measuring

In this paper1, we introduce a fuzzy automaton for computing the similar- ity between pairs of strings and a ge- netic method for adjusting its parame- ters. The fuzzy automaton models the edit operations needed to transform any string into another one. The selection of appropriate fuzzy operations and fuzzy membership values for the transitions leads to improve the system performance for a particular application.

A Fuzzy Approach to Approximate String Matching for Text Retrieval in NLP

Journal of Computational Information Systems , 2019

Approximate string matching has many applications in Natural Language Processing. This paper provides a comparison of various algorithms for approximate string matching. Most of the algorithms are based on the edit distance between characters in the two strings. It also covers the challenges in using these algorithms for the purpose of text retrieval. The authors propose an alternative approach for approximate string matching which are better suited for text retrieval. In this study we are comparing two strings to identify similarities using a matrix. The matrix will be updated for each overlap character between two strings. An overlap counter is maintained to increment value for each overlap character position and reset position to 0 when no overlap position is encountered. The maximum counter value is then used in a ratio to calculate the degree of similarity. The algorithm implemented using Python language. The results indicate the proposed approach can be used for identifying lexically similar words. This type of approach will find it use in lemmatization, text summarization, topic modelling and data mining solutions.

Fast String Searching Mechanism

Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology, 2015

A New Efficient Hybrid String Matching Algorithm to Solve the Exact String Matching Problem

The string matching algorithms are considered one of the most studied in the computer science field because the fundamental role they play in many different applications such as information retrieval, editors, security applications, firewall, and biological applications. This study aims to introduce a new hybrid algorithm based on two well-known algorithms, namely, the modified Horspool and SSABS hybrid algorithms. Two factors used to analyze the proposed algorithm which is the total number of character comparisons and total number of attempts. The ABSBMH algorithm which is the name chosen for the proposed hybrid algorithm was tested on different types of standard datatype. The ABSBMH algorithm shows less number of character comparisons when compared to the results of other algorithms, while show almost no big different in the results of number of attempts this is due to the proposed hybrid algorithm preprocessing phase based on SSABS algorithm which is the same preprocessing phase of the Quick Search algorithm, so for all these reasons the results of the ABSBMH and other algorithms in terms of total number of attempts have been shown a small different, this is because it use different pattern lengths which are selected randomly from the databases. The experiential results expose that