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Data mining in reaction databases: extraction of knowledge on chemical functionality transformations

Abstract : In this report, we present an experiment on knowledge discovery in chemical reaction databases. Chemical reactions are the main elements on which relies synthesis in organic chemistry, and this is why chemical reactions databases are of first importance. From a problem-solving process perspective, synthesis in organic chemistry must be considered at several levels of abstraction: mainly a strategic level where general synthesis methods are involved, and a tactic level where actual chemical reactions are applied. The research work presented in this paper is aimed at discovering general synthesis methods from chemical reaction databases in order to design generic and reusable synthesis plans. The knowledge discovery process relies on frequent level wise itemset search and association rule extraction, but also on chemical knowledge involved within every step of the knowledge discovery process. Moreover, the overall process is supervised by an expert of the domain. The principles of this original experiment on mining chemical reaction databases and its results are detailed and discussed.
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Submitted on : Tuesday, September 26, 2006 - 9:55:00 AM
Last modification on : Saturday, October 16, 2021 - 11:26:08 AM
Long-term archiving on: : Friday, November 25, 2016 - 12:16:08 PM


  • HAL Id : inria-00099862, version 1



Sandra Berasaluce, Gilles Niel, Amedeo Napoli, Claude Laurenço. Data mining in reaction databases: extraction of knowledge on chemical functionality transformations. [Intern report] A04-R-049 || berasaluce04a, 2004, 28 p. ⟨inria-00099862⟩



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