Knowledge discovery in databases: application to chromatography

Bryant, CH; Rowe, RC

Abstract

This paper reviews emerging computer techniques for discovering knowledge from databases and their application to various sets of separation data. The data-sets include the separation of a diverse range of analytes using either liquid, gas or ion chromatography. The main conclusion is that the new techniques should help to close the gap between the rate at which chromatographic data is gathered and stored electronically and the rate at which it can be analysed and understood.

Citation

Bryant, C., & Rowe, R. (1998). Knowledge discovery in databases: application to chromatography. Trends in Analytical Chemistry, 17(1), 18-24. https://doi.org/10.1016/S0165-9936%2897%2900094-0

• Journal Article Type: Article
• Online Publication Date: May 27, 1998
• Publication Date: May 27, 1998
• Deposit Date: Feb 17, 2009
• Publicly Available Date: Feb 17, 2009
• Journal: Trends in Analytical Chemistry
• Print ISSN: 0167-2940
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Issue: 1
• Pages: 18-24
• DOI: https://doi.org/10.1016/S0165-9936%2897%2900094-0
• Keywords: knowledge discovery in databases, machine learning, chromatography
• Publisher URL: http://dx.doi.org/10.1016/S0165-9936(97)00094-0