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Output details

11 - Computer Science and Informatics

Imperial College London

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Output 38 of 201 in the submission
Article title

Automated Discovery of Food Webs from Ecological Data Using Logic-Based Machine Learning

Type
D - Journal article
Title of journal
PLOS One
Article number
ARTN e29028
Volume number
6
Issue number
12
First page of article
-
ISSN of journal
1932-6203
Year of publication
2011
URL
-
Number of additional authors
4
Additional information

<28>Within Ecology the network of predation relations between species is known as a Food Web. This is key to understanding the effects of agriculture on the environment. However, detailed Food Webs are rare in the Environmental literature since each link requires intensive field studies. This paper is the first demonstration that a detailed Food Web can be automatically extracted from Large-Scale Farm study data using a machine learning algorithm, and it correlates strongly with links suggested within the literature. The research was conducted at Syngenta University Innovation Centre Imperial College and the three industrial co-authors are from Syngenta.

Interdisciplinary
Yes
Cross-referral requested
-
Research group
A - Logic and Artificial Intelligence
Citation count
3
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-