Towards Tractable and Practical ABox Abduction over Inconsistent Description Logic Ontologies
Authors: Jianfeng Du, Kewen Wang, Yi-Dong Shen
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results on benchmarks of inconsistent ontologies show that the proposed method scales to tens of millions of assertions and can be of practical use. |
| Researcher Affiliation | Academia | Jianfeng Du Guangdong University of Foreign Studies, Guangzhou 510006, China jfdu@gdufs.edu.cn Kewen Wang Griffith University, Brisbane, QLD 4111, Australia k.wang@griffith.edu.au Yi-Dong Shen State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China ydshen@ios.ac.cn |
| Pseudocode | No | The paper describes the proposed method verbally and via theorems, but does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper states 'We implemented the proposed method...in Java, using the Requiem...API...and the My SQL system...' but does not provide a link to the open-source code for their implementation. |
| Open Datasets | Yes | Six benchmark ontologies that are almost first-order rewritable were used. One is Semintec and the others are LUBMn (n = 1, 5, 10, 50, 100) from the Lehigh University Benchmark (Guo, Pan, and Heflin 2005) |
| Dataset Splits | No | The paper describes the benchmark ontologies and the generation of BCQs for observations, but it does not specify explicit training, validation, or test dataset splits in terms of percentages or sample counts for reproducing the experiments. |
| Hardware Specification | Yes | All experiments were conducted on a laptop having Dual-Core 2.20GHz CPU and 4GB RAM, with the maximum Java heap size set to 1GB. |
| Software Dependencies | No | The paper mentions software components like 'Java', 'Requiem API', and 'My SQL system' but does not provide specific version numbers for these dependencies. |
| Experiment Setup | Yes | For each Semintec+m ontology, we used the same 50 BCQs as observations, where ten BCQs were randomly generated from each of the five benchmark conjunctive queries (CQs) of Semintec... We set a time limit of 1000 seconds for handling one BCQ. |