Hilbert exclusion : improved metric search through finite isometric embeddings
- Submitting institution
-
University of St Andrews
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 267821376
- Type
- D - Journal article
- DOI
-
10.1145/3001583
- Title of journal
- ACM Transactions on Information Systems
- Article number
- 17
- First page
- -
- Volume
- 35
- Issue
- 3
- ISSN
- 1046-8188
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2016
- 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
-
3
- Research group(s)
-
B - Systems
- Citation count
- 13
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This article was the first to show how, in metric search, the four-point property of non-Euclidean spaces may be used to give a significant advantage over triangle inequality. Fourteen citing papers rely upon this property to develop further research. The article is extended from a conference paper which won the best paper award at SISAP16, Tokyo - a single award, in the context of over 100 submissions to the conference. An invited presentation of the journal paper was given at SIGIR19, Ann Arbor.
[http://www.sisap.org/2016/awards.html]
[http://sigir.org/sigir2018/program/program-at-a-glance/#s7b]
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
