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• W2465758885 abstract "Substructure search (SSS) is a fundamental technique supported by various chemical information systems. Many users apply it in an iterative manner: they modify their queries to shape the composition of the retrieved hit sets according to their needs. We propose and evaluate two heuristic extensions of SSS aimed at simplifying these iterative query modifications by collecting additional information during query processing and visualizing this information in an intuitive way. This gives the user a convenient feedback on how certain changes to the query would affect the retrieved hit set and reduces the number of trial-and-error cycles needed to generate an optimal search result. The proposed heuristics are simple, yet surprisingly effective and can be easily added to existing SSS implementations." @default.
• W2465758885 created "2016-07-22" @default.
• W2465758885 creator A5015583013 @default.
• W2465758885 date "2016-07-01" @default.
• W2465758885 modified "2023-09-27" @default.
• W2465758885 title "Guided Iterative Substructure Search (GI-SSS) - A New Trick for an Old Dog" @default.
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• W2465758885 doi "https://doi.org/10.1002/minf.201600063" @default.
• W2465758885 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27492243" @default.
• W2465758885 hasPublicationYear "2016" @default.
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