doi: 10.4304/jsw.9.10.2721-2731
Approximate String Similarity Join using Hashing Techniques under Edit Distance Constraints
- 1 College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
- 2 College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Abstract
The string similarity join, which is employed to find similar string pairs from string sets, has received extensive attention in database and information retrieval fields. To this problem, the <em>filter-and-refine</em> framework is usually adopted by the existing research work firstly, and then various filtering methods have been proposed. Recently, tree based index techniques with the edit distance constraint are effectively employed for evaluating the string similarity join. However, they do not scale well with large distance threshold. In this paper, we propose an efficient framework for approximate string similarity join based on Min-Hashing locality sensitive hashing and <em>trie</em>-based index techniques under string edit distance constraints. We show that our framework is flexible between trading the efficiency and performance. An empirical study using the real datasets demonstrates that our framework is more efficient and scales better.
Keywords
- Approximate String Similarity Join
- Loca
How to Cite
Peisen Yuan, Haoyun Wang, Jianghua Che, Shougang Ren, Huanliang Xu, and Dechang Pi, "Approximate String Similarity Join using Hashing Techniques under Edit Distance Constraints," Journal of Software, vol. 9, no. 10, pp. 2721-2731, 2014. https://doi.org/ 10.4304/jsw.9.10.2721-2731
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).