Query inseparability for ALC ontologies
- Submitting institution
-
Birkbeck College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 208
- Type
- D - Journal article
- DOI
-
10.1016/j.artint.2018.09.003
- Title of journal
- Artificial Intelligence
- Article number
- -
- First page
- 1
- Volume
- 272
- Issue
- -
- ISSN
- 0004-3702
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2019
- URL
-
http://eprints.bbk.ac.uk/id/eprint/24607/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
3 - Knowledge Representation and Data Management
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper obtains the first fundamental query entailment and inseparability results for non-Horn ontologies. Initial results were presented in paper accepted to IJCAI 2016.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -