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A Provenance-based Semantic Approach to Support Understandability, Reproducibility, and Reuse of Scientific Experiments
A Subjective Logic based Approach to Handling Inconsistencies in Ontology Merging
Accessing and Integrating Citizen Science Sensor Data: Evaluation of OGC Sensor Observation Service Implementations
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
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GMRs: Reconciliation of Generic Merge Requirements in Ontology Integration
Measuring Morphological Functional Leaf Traits From Digitized Herbarium Specimens Using TraitEx Software
On Using Subjective Logic to Build Consistent Merged Ontologies
Partitioning of BioPortal Ontologies: An Empirical Study
Semantic Relatedness as an Inter-Facet Metric for Facet Selection over Knowledge Graphs
Species Association Knowledge Graph Construction – A Demo Paper
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 |
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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 |