Thumbnail Image
Publication

Simple algorithms for predicate suggestions using similarity and co-occurrence

Oren, Eyal
; 
Gerke, Sebastian
; 
Decker, Stefan
Files
Thumbnail Image
eswc2007.pdf
Adobe PDF, 965.29 KB
Citations
Altmetric:
Identifiers
http://hdl.handle.net/10379/540
 https://doi.org/10.13025/20994
Publication Date
2007
Keywords
Data Science Institute
Type
conference paper
Downloads
Show all metadata
Citation
Eyal Oren, Sebastian Gerke, Stefan Decker "Simple algorithms for predicate suggestions using similarity and co-occurrence", Proceedings of the European Semantic Web Conference, 2007.
Abstract
When creating Semantic Web data, users have to make a critical choice for a vocabulary: only through shared vocabularies can meaning be established. A centralised policy prevents terminology divergence but would restrict users needlessly. As seen in collaborative tagging environments, suggestion mechanisms help terminology convergence without forcing users. We introduce two domain-independent algorithms for recommending predicates (RDF statements) about resources, based on statistical dataset analysis. The first algorithm is based on similarity between resources, the second one is based on co-occurrence of predicates. Experimental evaluation shows very promising results: a high precision with relatively high recall in linear runtime performance.
Funder
m3pe
Science Foundation Ireland
Publisher
Association for Computing Machinery
Publisher DOI
Rights
CC BY-NC-ND
cbn
Collections
Publications