Ontology-Mediated Query Answering over Log-Linear Probabilistic Data
Authors: Stefan Borgwardt, İsmail İlkan Ceylan, Thomas Lukasiewicz2711-2718
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We propose a new data model that integrates the paradigm of ontology-mediated query answering with probabilistic databases, employing a log-linear probability model. We compare our approach to existing proposals, and provide supporting computational results. and We obtain a host of complexity results. |
| Researcher Affiliation | Academia | Stefan Borgwardt Faculty of Computer Science Technische Universit at Dresden, Germany stefan.borgwardt@tu-dresden.de Ismail Ilkan Ceylan, Thomas Lukasiewicz Department of Computer Science University of Oxford, UK ismail.ceylan@cs.ox.ac.uk thomas.lukasiewicz@cs.ox.ac.uk |
| Pseudocode | No | The paper describes theoretical models and reductions but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | We leave as future work an implementation, combining existing gradient-based optimization methods with efficient rewriting techniques and PDB or MLN inference engines. |
| Open Datasets | No | The paper is theoretical and does not conduct empirical experiments with a training dataset. It references existing probabilistic knowledge bases as sources for data for a theoretical learning approach, but not for empirical training. |
| Dataset Splits | No | The paper is theoretical and does not conduct empirical experiments, therefore no training/validation/test splits are provided. |
| Hardware Specification | No | The paper is theoretical and does not describe experimental hardware specifications. |
| Software Dependencies | No | The paper is theoretical and explicitly states that implementation is future work, therefore no specific software dependencies with version numbers are provided. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details or hyperparameters. |