Combinatorial Clustering of Coastal Contaminant Data an Extended Abstract
This empirical study demonstrate the effectiveness of correlation clustering that allows overlapping via graph-theoretic algorithms to cluster data collected by multiple monitoring & assessment stations of the US National Oceanographic and Atmospheric Administration (NOAA) to characterize polycyclic aromatic hydrocarbon mixtures in bivales.
Authors
- Joseph R. Barr
- Kimani L. Kimbrough
- Faisal N. Abu-Khzam (ORCID: https://orcid.org/0000-0001-5221-8421)
Institutions
- National Oceanic and Atmospheric Administration (US)
- Lebanese American University (LB)
Publication Details
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1109/aixset62544.2024.00055
- Primary Topic
- Data Management and Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00