Open AccessJaro–Winkler Distance Improvement For Approximate String Search Using Indexing Data For Multiuser Application
Author(s) -
F. Friendly
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1361/1/012080
Subject(s) - jaccard index , edit distance , search engine indexing , hamming distance , lexicographical order , computer science , similarity (geometry) , mathematics , information retrieval , artificial intelligence , algorithm , pattern recognition (psychology) , combinatorics , image (mathematics)
Word searching method has been developed in many ways and named as: Hamming Distance, Jaccard Distance, Jaro Distance, Jaro-Winkler Distance, Levenshtein Distance, etc. Those methods are used for lexicographic comparison to find words according to the similarity of the words which searched. The time needed for searching by using these words distance method can cause overhead as some difference user might try to search the same words all over. If these method is used in a multi user application where the user generally searching for some keywords repeatedly, then the user might have a longer searching time compared to exact search. In spite of this problem, we try to propose a method where the first search result of the previous user, will be recorded to the database for future usage by indexing the search keywords. In order to try this method, we use Jaro-winkler Distance method to search words. From the test result show that combining indexing and similarity word searching by using Jaro-Winkler Distance method can decrease the searching time to 90-92% compared to just using the Jaro-Winkler Distance method only. As the searched data increased, the processing time can be shorten.