header

Parallel Tractability of Ontology Materialization: Technique and Practice

43 Pages Posted: 16 Oct 2018 Publication Status: Accepted

See all articles by Zhangquan Zhou

Zhangquan Zhou

Southeast University - School of Computer Science and Engineering

Guilin Qi

Southeast University - School of Computer Science and Engineering

Birte Glimm

Ulm University - Institute of Artificial Intelligence

Abstract

Materialization is an important reasoning service for many ontology-based applications, but the rapid growth of semantic data poses the challenge to efficiently perform materialization on largescale ontologies. Parallel materialization algorithms work well for some ontologies, although the reasoning problem for the used ontology language is not in NC, i.e., the theoretical complexity class for parallel tractability. This motivates us to study the problem of parallel tractability of ontology materialization from a theoretical perspective. We focus on the datalog rewritable ontology languages DL-Lite and Description Horn Logic (DHL) and propose algorithms, called NC algorithms, to identify classes of ontologies for which materialization is tractable in parallel. To verify the practical usability of the above results, we analyze different benchmarks and realworld datasets, including LUBM and the YAGO ontology, and show that for many ontologies expressed in DHL materialization is tractable in parallel. The implementation of our optimized parallel algorithm shows performance improvements over the highly optimized state-of-the-art reasoner RDFox on ontologies for which materialization is tractable in parallel.

Keywords: ontology, materialization, datalog, parallel tractability, NC complexity

Suggested Citation

Zhou, Zhangquan and Qi, Guilin and Glimm, Birte, Parallel Tractability of Ontology Materialization: Technique and Practice (October 16, 2018). Available at SSRN: https://ssrn.com/abstract=3267164 or http://dx.doi.org/10.2139/ssrn.3267164

Zhangquan Zhou (Contact Author)

Southeast University - School of Computer Science and Engineering ( email )

Sipailou 2#
Nanjing, Jiangsu Province 210096
China

Guilin Qi

Southeast University - School of Computer Science and Engineering ( email )

Sipailou 2#
Nanjing, Jiangsu Province 210096
China

Birte Glimm

Ulm University - Institute of Artificial Intelligence ( email )

Albert-Einstein-Alee 11
Ulm, Baden-Württemberg D-89081
Germany

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
39
Abstract Views
557
PlumX Metrics