An accurate toponym-matching measure based on approximate string matching

• Published in: Journal of information science Vol. 42; no. 2; pp. 138 - 149
• Main Author: Kilinc, Deniz
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.04.2016; Bowker-Saur Ltd
• Subjects: Approximate string matching; Computer science; Datasets; Information retrieval; Matching; Names; Phases; Recall; Sentences; Similarity; String matching; Strings; Studies; Approximate string matching; geographic information retrieval; toponym matching
• ISSN: 0165-5515; 1741-6485
• DOI: 10.1177/0165551515590097

Approximate string matching (ASM) is a challenging problem, which aims to match different string expressions representing the same object. In this paper, detailed experimental studies were conducted on the subject of toponym matching, which is a new domain where ASM can be performed, and the creation of a single string-matching measure that can perform toponym matching process regardless of the language was attempted. For this purpose, an ASM measure called DAS, which comprises name similarity, word similarity and sentence similarity phases, was created. Considering the experimental results, the retrieval performance and system accuracy of DAS were much better than those of other well-known five measures that were compared on toponym test datasets. In addition, DAS had the best metric values of mean average precision in six languages, and precision/recall graphs confirm this result.