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- W2183857233 abstract "In the last few years a number of different sub- gr aph mining algorithms have been proposed. They are often used for finding frequent fragments in molecular databases. All these algorithms behave quite well when used on small datasets of not more than a few thousand molecules. How- ever, they all fail on larger amounts of data because they are either time consuming or have enormous memory require- ments. In this paper we present a hybrid mining technique that overcomes the individual problems of the underlying algorithms and outperforms the individual methods impres- sively on large databases." @default.
- W2183857233 created "2016-06-24" @default.
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- W2183857233 date "2004-01-01" @default.
- W2183857233 modified "2023-09-27" @default.
- W2183857233 title "Hybrid fragment mining with MoF a and FSG" @default.
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