3 ms·
Ask HN: Perspectives on graph-bound logical inference
I am researching graph processing (OLTP) and graph databases for a system where semanticity is inherent.
I am currently exploring logical inference (or reasoning) (Stardog [1], GraphDB [2], Grakn [3]) and stumbled upon «The Semantic Web, Syllogism, and Worldview» (2003) [0].
Semantics aside (this system would mandate for Stardog and Grakn’s lazy reasoning rather than GraphDB’s total materialization), I am interested in practical analyses of logical inference as I find some [0] arguments to be sound and atemporal and am therefore “undirected.”
Although it does not support automatic reasoning, Datomic [4] viewpoints are welcome.
- wll 9y ago[0] http://web.archive.org/web/20180311022804/http://www.shirky.com/writings/herecomeseverybody/semantic_syllogism.html http://web.archive.org/web/20180311022804/http://www.shirky.... [1] https://www.stardog.com/docs/#_owl_rule_reasoning https://www.stardog.com/docs/#_owl_rule_reasoning [2] http://graphdb.ontotext.com/documentation/enterprise/reasoning.html http://graphdb.ontotext.com/documentation/enterprise/reasoni... [3] http://dev.grakn.ai/docs/knowledge-model/inference http://dev.grakn.ai/docs/knowledge-model/inference [4] https://docs.datomic.com/on-prem/query.html https://docs.datomic.com/on-prem/query.html