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A Subjective Logic based Approach to Handling Inconsistencies in Ontology Merging- ADOnIS: Managing Critical Zone Research Data Using Semantic Web Technologies
- Automatic Facet Generation and Selection over Knowledge Graphs
- Building Ontologies for Reuse – Lessons Learned from Unit Ontologies
- Efficient Bounded Jaro-Winkler Similarity Based Search
- Eleven years’ data of grassland management in Germany
- Entity Extraction in the Ecological Domain – A practical guide
- GMRs: Reconciliation of Generic Merge Requirements in Ontology Integration
- On Using Subjective Logic to Build Consistent Merged Ontologies
- Semantic Relatedness as an Inter-Facet Metric for Facet Selection over Knowledge Graphs
- Towards an ecological trait‐data standard
- Towards Knowledge Graph Construction using Semantic Data Mining
Efficient Bounded Jaro-Winkler Similarity Based Search
| Title: | Efficient Bounded Jaro-Winkler Similarity Based Search |
|---|---|
| Authors: | Jan Martin Keil |
| Source: | 18. Fachtagung "Datenbanksysteme für Business, Technologie und Web" (BTW) |
| Date: | 2019-03-07 |
| Type: | Conference Paper |
| Abstract: |
The Jaro-Winkler similarity is a widely used measure for the similarity of strings. We propose an efficient algorithm for the bounded search of similar strings in a large set of strings. We compared our approach to the naive approach and the approach by Dreßler et al. Our results prove a significant improvement of the efficiency in computation of the bounded Jaro-Winkler similarity for querying of similar strings. |
| File: | Efficient Bounded Jaro-Winkler Similarity Based Search |
| URL: | https://doi.org/10.18420/btw2019-13 |