Towards context-aware similarity metrics

被引:0
作者
Morent, D [1 ]
Patterson, DE [1 ]
Berthold, MR [1 ]
机构
[1] Univ Konstanz, ALTANA, Chair Bioinformat & Informat Min, Dept Comp & Informat Sci, D-78457 Constance, Germany
来源
Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vols 1-9 | 2005年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Comparing molecular structures is often done based on relatively high-dimensional, binary fingerprints that represent absence or presence of certain structural elements. The then commonly used Tanimoto distance considers all those bits similar, although some of the underlying structural elements may be quite closely related. We propose a weighting scheme for such related bits which softens the influence of differences in bit patterns that represent similar contexts. We demonstrate the usefulness of this context aware similarity metric using an automated bit-weighting mechanism and a set of similarity weights based on Topomer shape similarity between the structural elements encoded in the finger print.
引用
收藏
页码:5596 / 5598
页数:3
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