Learning Conceptual Space Representations of Interrelated Concepts
Authors: Zied Bouraoui, Steven Schockaert
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section, we experimentally evaluate our method2 against a number of baseline methods. |
| Researcher Affiliation | Academia | Zied Bouraoui CRIL CNRS & Univ Artois, France bouraoui@cril.univ-artois.fr Steven Schockaert Cardiff University, UK Schockaert S1@Cardiff.ac.uk |
| Pseudocode | No | The paper describes the proposed methods using text and mathematical equations, but does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | Implementation and data available at https://github.com/flexilogalgo |
| Open Datasets | Yes | In our experiments, we have used SUMO3, which is a large open-domain ontology. ... SUMO3, http://www.adampease.org/OP/. Babel Net4, Babel Net Java API available at http://babelnet.org |
| Dataset Splits | Yes | We split the set of individuals into a training set Itrain containing 2/3 of all individuals, and a test set Itest containing the remaining 1/3. |
| Hardware Specification | No | The paper does not provide any specific details regarding the hardware used for the experiments, such as CPU or GPU models. |
| Software Dependencies | No | The paper mentions using Babel Net Java API, but does not specify its version or any other software dependencies with version numbers. |
| Experiment Setup | Yes | The number of Gibbs sample that we used is equal to 1000 where each sample is generated after 25 every 25 iterations. The burn-in period that we use is fixed to 200 samples. |