7 citations · 13 across the 7 of their papers we have counts for
7 papers
Optimised Storage for Datalog Reasoning
Xinyue Zhang, Pan Hu, Yavor Nenov +1
Materialisation facilitates Datalog reasoning by precomputing all consequences of the facts and the rules so that queries can be directly answered over the materialised facts. Howe…
Enhancing Datalog Reasoning with Hypertree Decompositions
Xinyue Zhang, Pan Hu, Yavor Nenov +1
Datalog reasoning based on the seminaïve evaluation strategy evaluates rules using traditional join plans, which often leads to redundancy and inefficiency in practice, especially…
MeTeoR: Practical Reasoning in Datalog with Metric Temporal Operators
Dingmin Wang, Pan Hu, Przemysław Andrzej Wałęga +1
DatalogMTL is an extension of Datalog with operators from metric temporal logic which has received significant attention in recent years. It is a highly expressive knowledge repres…
OWL2Vec*: Embedding of OWL Ontologies
Jiaoyan Chen, Pan Hu, Ernesto Jimenez-Ruiz +3
Semantic embedding of knowledge graphs has been widely studied and used for prediction and statistical analysis tasks across various domains such as Natural Language Processing and…
Datalog Reasoning over Compressed RDF Knowledge Bases
Pan Hu, Jacopo Urbani, Boris Motik +1
Materialisation is often used in RDF systems as a preprocessing step to derive all facts implied by given RDF triples and rules. Although widely used, materialisation considers all…
Modular Materialisation of Datalog Programs
Pan Hu, Boris Motik, Ian Horrocks
The seminaïve algorithm can materialise all consequences of arbitrary datalog rules, and it also forms the basis for incremental algorithms that update a materialisation as the inp…
Optimised Maintenance of Datalog Materialisations
Pan Hu, Boris Motik, Ian Horrocks
To efficiently answer queries, datalog systems often materialise all consequences of a datalog program, so the materialisation must be updated whenever the input facts change. Seve…