Dr Taoxin Peng T.Peng@napier.ac.uk
Lecturer
An evaluation of name matching techniques.
Peng, Taoxin; Li, Lin; Kennedy, Jessie
Authors
Lin Li
Prof Jessie Kennedy J.Kennedy@napier.ac.uk
Enhanced Associate
Abstract
Abstract—There is a growing awareness that the high quality of string matching is a key to a variety of applications, such as data integration, text and web mining, information retrieval, search engine. In such applications, matching names is one of the popular tasks. There are a number of name matching techniques available. Unfortunately, there is no existing name matching technique that performs the best in all situations. Different techniques perform differently in different situations. Therefore, a problem that every researcher or a practitioner has to face is how to select an appropriate technique for a given dataset. This paper analyzes and evaluates a set of popular name matching techniques on several carefully designed different datasets. The experimental comparison confirms the statement that there is no clear best technique. Some suggestions have been presented, which can be used as guidance for researchers and practitioners to select an appropriate name matching technique in a given dataset.
Citation
Peng, T., Li, L., & Kennedy, J. (2011). An evaluation of name matching techniques. In Proceedings of 2nd Annual International Conference on Business Intelligence and Data Warehousing
Start Date | Jun 27, 2011 |
---|---|
End Date | Jun 28, 2011 |
Publication Date | 2011 |
Deposit Date | Mar 6, 2012 |
Peer Reviewed | Peer Reviewed |
Book Title | Proceedings of 2nd Annual International Conference on Business Intelligence and Data Warehousing |
ISBN | 978-981-08-9266-1 |
Keywords | String matching; data integration; data mining; information retrieval; name matching techniques; |
Public URL | http://researchrepository.napier.ac.uk/id/eprint/4994 |
You might also like
A comparison of techniques for name matching
(2012)
Journal Article
Data quality and data cleaning in database applications
(2012)
Thesis
A rule based taxonomy of dirty data.
(2011)
Journal Article
Improving data quality in data warehousing applications
(2010)
Conference Proceeding
Developing Visualisations to Enhance an Insider Threat Product: A Case Study
(2021)
Conference Proceeding
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search