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A machine learning approach to weighting schemes in the data fusion of similarity coefficients

Chen, J., Holliday, J.D. and Bradshaw, J. (2009) A machine learning approach to weighting schemes in the data fusion of similarity coefficients. Journal of Chemical Information and Modeling, 49 (2). pp. 185-194. ISSN 1549-9596

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Abstract

The application of data fusion techniques for combining the results of similarity searches of chemical databases has been shown to improve search performance. When used to combine the results of searches using different similarity coefficients, the optimum combination is dependent on the size, in terms of substructural fragments present, of the molecules being compared. This paper describes preliminary simulation tests which aim to automatically deduce, using machine learning techniques, the optimum combination of similarity coefficient which may be combined using data fusion for a given class of active compounds.

Item Type: Article
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
Depositing User: Information Studies
Date Deposited: 25 Aug 2009 14:33
Last Modified: 25 Aug 2009 14:33
Published Version: http://dx.doi.org/10.1021/ci800292d
Status: Published
Publisher: American Chemical Society
Identification Number: 10.1021/ci800292d
URI: http://eprints.whiterose.ac.uk/id/eprint/9222

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