Paper Info
Title
Discriminant temporal patterns for linking physico-chemistry and biology in hydro-ecosystem assessment.
Abstract
We propose a new data mining process to extract original knowledge from hydro-ecological data, in order to help the identification of pollution sources. This approach is based (1) on a domain knowledge discretization (quality classes) of physico-chemical and biological parameters, and (2) on an extraction of temporal patterns used as discriminant features to link physico-chemistry with biology in river sampling sites. For each bio-index quality value, we obtained a set of significant discriminant features. We used them to identify the physico-chemical characteristics that impact on different biological dimensions according to their presence in extracted knowledge. The experiments meet with the domain knowledge and also highlight significant mismatches between physico-chemical and biological quality classes. Then, we discuss about the interest of using discriminant temporal patterns for the exploration and the analysis of temporal environmental data such as hydro-ecological databases.
Year
DOI
Venue
2014
10.1016/j.ecoinf.2014.09.003
Ecological Informatics
Keywords
Field
DocType
Data mining,Temporal patterns,Discriminant patterns,Hydro-ecology,River quality
Data mining,Discretization,Domain knowledge,Discriminant,Computer science,Sampling (statistics),Environmental data,Ecosystem
Journal
Volume
ISSN
Citations 
24
1574-9541
3
PageRank 
References 
Authors
0.45
10
7
Name
Order
Citations
PageRank
Mickaël Fabrègue1132.34
Agnès Braud25113.41
Sandra Bringay318334.40
Corinne Grac4204.37
Florence Le Ber513529.28
Danielle Levet630.45
Maguelonne Teisseire7557129.00