Consistent Knowledge Discovery from Evolving Ontologies
Authors: Freddy Lecue, Jeff Pan
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The experiments have shown scalable, accurate and consistent knowledge discovery with data from Dublin." and "We report (i) scalability, (ii) accuracy of Algorithm 3 (noted [A3]). The experiments have been conducted on a server of 4 Intel(R) Xeon(R) X5650, 2.67GHz cores, 6GB RAM. |
| Researcher Affiliation | Collaboration | Freddy L ecu e IBM Dublin Research Center, Ireland freddy.lecue@ie.ibm.com" and "Jeff Z.Pan University of Aberdeen, UK jeff.z.pan@abdn.ac.uk |
| Pseudocode | Yes | The paper includes 'Algorithm 1: atomsets-mining', 'Algorithm 2: Atomsets Generation', and 'Algorithm 3: CIKD' with structured steps. |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | No | The paper mentions using 'Dynamic data: [a] weather, [b] travel time, [c] incident, [d] event, [e] bus location in Dublin (Table 3)', but it does not provide concrete access information (link, DOI, specific repository, or formal citation for public access) for this dataset. |
| Dataset Splits | No | The paper mentions 'We used a fixed (off-line) window of n = 4, 320 snapshots (48 hours) for mining' and 'Accuracy is measured by validating induced knowledge over 10, 000 past situations where buses status is known.' However, it does not provide specific train/test/validation split percentages, absolute sample counts, or references to predefined splits needed to reproduce the data partitioning. |
| Hardware Specification | Yes | The experiments have been conducted on a server of 4 Intel(R) Xeon(R) X5650, 2.67GHz cores, 6GB RAM. |
| Software Dependencies | No | The paper mentions various techniques and frameworks like 'OWL 2', 'DL EL++', 'WARMR', and 'ap-genrules' as parts of its methodology, but it does not provide specific version numbers for any software dependencies or libraries used in its implementation or experiments. |
| Experiment Setup | Yes | The paper specifies experimental parameters such as '(σmin, ωmin, γmin) being (1/2, n, (2/3, 3/4))' for Algorithm 3 and details in Table 4 (e.g., 'σmin .4 .4 .4 .4 .8 .8 .8 .8' and 'γmin (.4, .4) (.4, .8) (.8, .4) (.8, .8)'). |