Handling scalable approximate queries over NoSQL graph databases: : Cypherf and the Fuzzy4S framework
- Submitting institution
-
University of Bristol
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 160638152
- Type
- D - Journal article
- DOI
-
10.1016/j.fss.2017.08.002
- Title of journal
- Fuzzy Sets and Systems
- Article number
- -
- First page
- 21
- Volume
- 348
- Issue
- -
- ISSN
- 0165-0114
- Open access status
- Deposit exception
- Month of publication
- August
- Year of publication
- 2017
- URL
-
-
- 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
-
1
- Research group(s)
-
A - Artificial Intelligence and Autonomy
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The system was designed in collaboration with Neo4J (Neo4J.com), a leading provider of NoSQL graph databases. It avoids the inefficiency of running multiple queries that is normally incurred by fuzzy query languages. The proposed approach is scalable, as shown by a set of experiments reported in the paper, and is applicable to big-data problems. External authors have proposed this work as a basis for fuzzy cloud-based queries (Yu et al, DOI: 10.1145/3207677.3278082).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -