Using Levenshtein Distance Algorithm to Increase Database Search Efficiency and Accuracy

الملخص

Names are frequently used as a search criterion in databases to retrieve information, so names play an important role in information systems, but some names in the case of application may have some defects, including misspellings, in addition to those cultural differences complicate the retrieval of information Based on names. In a string fuzzy match, the goal is to find short text matches from many long texts, in which case fewer matches in variance are expected. For example, a short text can come from a dictionary, here usually one of the strings is short and the other is arbitrarily long. Levinstein's space has a wide range of applications, such as spell checking, optical character correction systems, and memorybased natural language translation utilities. In this paper, the Levenstein algorithm was used and included in the SQL Server database engine. The purpose of this is to combine the queries with Levenstein's algorithm to obtain the best search results and to compare them with the results of traditional search and filtering in queries. The results were better in terms of accessing the required records, but that was at the expense of the time it takes to get the results.