Hashing Questions Medium
A hash-based approximate string matching algorithm is a technique used to find similarities or matches between two strings, even when they are not exactly the same. It involves the use of hash functions to convert strings into fixed-length hash codes or signatures, which can be compared to identify potential matches.
The algorithm works by dividing the strings into smaller substrings or chunks and generating hash codes for each of these substrings. These hash codes are then compared to quickly identify potential matches. If two substrings have the same hash code, it indicates a potential match, and further detailed comparison can be performed to confirm the similarity.
One common hash-based approximate string matching algorithm is the n-gram technique. In this approach, the strings are divided into n-grams, which are contiguous sequences of n characters. Hash codes are generated for each n-gram, and these codes are compared to identify potential matches. By varying the value of n, the algorithm can be tuned to capture different levels of similarity between strings.
Hash-based approximate string matching algorithms are efficient and scalable, as the use of hash codes allows for quick comparison and filtering of potential matches. They are commonly used in applications such as spell checking, plagiarism detection, DNA sequence matching, and text mining. However, it is important to note that these algorithms provide approximate matches and may have some false positives or false negatives, depending on the chosen hash function and matching criteria.