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This is one of R12.2.5 Enhancement in EBS AR.
The Automatic Cash Application improves accuracy and on-time application of cash receipts with the introduction of two new methods for automatically applying cash receipts.
- The first method generates match scores using the Levenshtein distance algorithm and automatically applies the receipt based on a score threshold.
- The second methods applies receipts by knap sacking the receipt amount and the open transactions of the customer.
Both methods provide suggested matches when a receipt cannot be applied automatically
Background information on the Levenshtein distance algorithm [ From Wikipedia, the free encyclopedia ]
In information theory and computer science, the Levenshtein distance is a metric for measuring the amount of difference between two sequences (i.e., the so called edit distance).
The Levenshtein distance between two strings is given by the minimum number of operations needed to transform one string into the other, where an operation is an insertion, deletion, or substitution of a single character. A generalization of the Levenshtein distance (Damerau–Levenshtein distance) allows the transposition of two characters as an operation. Some Translation Environment Tools, such as translation memory leveraging applications, use the Levenhstein algorithm to measure the edit distance between two fuzzy matching content segments.
The metric is named after Vladimir Levenshtein, who considered this distance in 1965.It is often used in applications that need to determine how similar, or different, two strings are, such as spell checkers.
For example, the Levenshtein distance between "kitten" and "sitting" is 3, since the following three edits change one into the other, and there is no way to do it with fewer than three edits:
- kitten -> sitten (substitution of 's' for 'k')
- sitten -> sittin (substitution of 'i' for 'e')
- sittin -> sitting (insert 'g' at the end).