Embracing Change by Abstraction Materialization Maintenance for Large ABoxes
Authors: Markus Brenner, Birte Glimm
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our empirical evaluation with synthetic and real-world ontologies shows up to four times improved materialization times compared to the approach without Abstraction Reļ¬nement in different change scenarios.For the evaluation, we focus on directly comparing the algorithms, i.e. classical DRed and ARDRed. To do so, we have implemented both from scratch in Java including support for additions. The code and the experimental data are publicly available [Glimm and Brenner, 2018]. |
| Researcher Affiliation | Academia | Markus Brenner and Birte Glimm University of Ulm, Germany markus.brenner@uni-ulm.de, birte.glimm@uni-ulm.de |
| Pseudocode | Yes | Algorithm 1: materialize AR(O)Algorithm 2: DRed(O, A , A )Algorithm 3: ARDRed(O, A , A ) |
| Open Source Code | Yes | The code and the experimental data are publicly available [Glimm and Brenner, 2018]. |
| Open Datasets | Yes | As basis for the test cases, we used the UOBM benchmark [Ma et al., 2006], for which we generated instances of 10, 50 and 100 universities (denoted UOBM10, UOBM50, and UOBM100, respectively) and the well-known NPD and Reactome ontologies. |
| Dataset Splits | No | No explicit training, validation, or test dataset splits in terms of percentages or counts for distinct dataset portions were specified. The paper describes scenarios (add-only, remove-only, add-remove) and how ABoxes are changed over time for evaluation. |
| Hardware Specification | Yes | All tests were executed on a server with two Intel hexa core processors at 2.60GHz (without using parallelization) and each test execution was assigned 200 GB of the overall 500 GB RAM to allow for keeping all test data in memory to avoid I/O impact. |
| Software Dependencies | No | The implementation was done 'from scratch in Java' but no specific version numbers for Java or any other software dependencies were provided. |
| Experiment Setup | Yes | Each change ABox contains all assertions for 1% of the individuals from A. We evaluate three scenarios: (1) add-only starts with an almost empty A0 and step by step adds the change ABoxes; (2) remove-only starts with A0 = A and then removes the change ABoxes; (3) add-remove alternates between additions and removals, starting with two initial addition steps to avoid adding/removing the same individuals over and over again. |