Querying Inconsistent Description Logic Knowledge Bases under Preferred Repair Semantics
Authors: Meghyn Bienvenu, Camille Bourgaux, François Goasdoué
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | An experimental evaluation of the approach shows good scalability on realistic cases. Our second contribution is a practical approach to query answering in DL-Lite R under the AR, P -AR, and P -IAR semantics... An experimental evaluation demonstrates the scalability of the approach in settings we presume realistic. 6 Experimental Evaluation We implemented our query answering framework in Java within our CQAPri ( Consistent Query Answering with Priorities ) tool. |
| Researcher Affiliation | Academia | Meghyn Bienvenu and Camille Bourgaux LRI, CNRS & Universit e Paris-Sud Orsay, France Franc ois Goasdou e IRISA, Universit e de Rennes 1 Lannion, France |
| Pseudocode | No | No pseudocode or algorithm blocks are explicitly presented. |
| Open Source Code | No | We implemented our query answering framework in Java within our CQAPri ( Consistent Query Answering with Priorities ) tool. CQAPri is built on top of the relational database server Postgre SQL, the Rapid query rewriting engine for DL-Lite (Chortaras, Trivela, and Stamou 2011), and the SAT4J v2.3.4 SAT solver (Berre and Parrain 2010). |
| Open Datasets | Yes | We considered the modified LUBM benchmark from Lutz et al. (2013), which provides the DL-Lite R version LUBM 20 of the original LUBM ELI TBox, and the Extended University Data Generator (EUDG) v0.1a (both available at www.informatik.uni-bremen.de/ clu/combined). |
| Dataset Splits | No | Inconsistencies in the ABox were introduced by contradicting the presence of an individual in a concept assertion with probability p, and the presence of each individual in a role assertion with probability p/2. Additionally, for every role assertion, its individuals are switched with probability p/10. Prioritizations of ABox were made to capture a variety of scenarios. |
| Hardware Specification | No | No specific hardware details (like CPU/GPU models, memory, etc.) are mentioned for running experiments. |
| Software Dependencies | Yes | CQAPri is built on top of the relational database server Postgre SQL, the Rapid query rewriting engine for DL-Lite (Chortaras, Trivela, and Stamou 2011), and the SAT4J v2.3.4 SAT solver (Berre and Parrain 2010). |
| Experiment Setup | Yes | Inconsistencies in the ABox were introduced by contradicting the presence of an individual in a concept assertion with probability p, and the presence of each individual in a role assertion with probability p/2. Additionally, for every role assertion, its individuals are switched with probability p/10. Prioritizations of ABox were made to capture a variety of scenarios... Every ABox s id u Xp Y indicates the number X of universities generated by EUDG and the probability value Y of p for adding inconsistencies as explained above (Me-P reads M.10 P ).... We built 8 prioritizations for each of these ABoxes further denoted by the id of the ABox it derives from, and a suffix first indicating the number of priority levels and then how these levels were chosen. l Zd W indicates the number Z of priority levels: 3 and 10 in our experiments, and the distribution W: cr=, a=, cr =, or a = indicates whether priority levels were chosen per concept/role (cr) or assertion (a), and whether choosing between these levels was equiprobable (=) or not (=). |