Optimised Maintenance of Datalog Materialisations
Authors: Pan Hu, Boris Motik, Ian Horrocks
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We have implemented our hybrid algorithms and have compared them empirically. |
| Researcher Affiliation | Academia | Pan Hu, Boris Motik, Ian Horrocks Department of Computer Science, University of Oxford Oxford, United Kingdom firstname.lastname@cs.ox.ac.uk |
| Pseudocode | Yes | Algorithm 1 DRED(Π, λ, E, I, E , E+) |
| Open Source Code | Yes | Our test system and datasets are available online.1 |
| Open Datasets | Yes | We used the following benchmarks for our evaluation: UOBM (Ma et al. 2006) ... Reactome (Croft et al. 2013) ... Uniprot (Bateman et al. 2015) ... Chem BL (Gaulton et al. 2011) ... Claros ... and SSPE (Single-Source Path Enumeration). |
| Dataset Splits | No | The paper describes testing with small and large deletions but does not specify training, validation, or test dataset splits with percentages or counts. |
| Hardware Specification | Yes | We conducted all experiments on a Dell Power Edge R720 server with 256GB RAM and two Intel Xeon E5-2670 2.6GHz processors, running Fedora 24, kernel version 4.8.12-200.fc24.x86 64. |
| Software Dependencies | No | The paper mentions the operating system and kernel version ('Fedora 24, kernel version 4.8.12-200.fc24.x86 64') but does not provide specific software dependencies or libraries with version numbers (e.g., Python, PyTorch, TensorFlow, specific solvers). |
| Experiment Setup | Yes | All algorithms handle insertions using the semina ıve evaluation. The only overhead is in counter maintenance, which we measured during initial materialisation (which also uses semina ıve evaluation). Hence, the main focus of our tests was on comparing the performance of our algorithms on small and large deletions. In both cases, we first materialised the relevant program on the explicit facts, and then we performed the following tests. To test small deletions, we measured the performance on ten randomly selected subsets E E of 1,000 facts. |