Journal article
ENFrame: a framework for processing probabilistic data
- Abstract:
-
This article introduces ENFrame, a framework for processing probabilistic data. Using ENFrame, users can write programs in a fragment of Python with constructs such as loops, list comprehension, aggregate operations on lists, and calls to external database engines. Programs are then interpreted probabilistically by ENFrame. We exemplify ENFrame on three clustering algorithms (k-means, k-medoids, and Markov clustering) and one classification algorithm (k-nearest-neighbour).
A key co...
Expand abstract
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 890.9KB, Terms of use)
-
- Publisher copy:
- 10.1145/2877205
Authors
Funding
Bibliographic Details
- Publisher:
- Association for Computing Machinery
- Journal:
- ACM Transactions on Database Systems More from this journal
- Volume:
- 41
- Issue:
- 1
- Article number:
- 3
- Publication date:
- 2016-03-18
- Acceptance date:
- 2015-12-01
- DOI:
- EISSN:
-
1557-4644
- ISSN:
-
0362-5915
Item Description
- Language:
-
English
- Keywords:
- Pubs id:
-
pubs:609202
- UUID:
-
uuid:10f1d59b-d5f3-4a71-a19d-0f27c1140a59
- Local pid:
-
pubs:609202
- Source identifiers:
-
609202
- Deposit date:
-
2016-03-10
Terms of use
- Copyright holder:
- ACM
- Copyright date:
- 2016
- Rights statement:
- Copyright © 2016 ACM.
- Notes:
- This is the author accepted manuscript version of the article. The final version is available online from ACM at: http://dx.doi.org/10.1145/2877205
Metrics
If you are the owner of this record, you can report an update to it here: Report update to this record