Publikation: Towards context-aware similarity metrics (invited paper)
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2005
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2005 International Conference on Machine Learning and Cybernetics. IEEE, 2005, pp. 5596-5598 Vol. 9. ISBN 0-7803-9091-1. Available under: doi: 10.1109/ICMLC.2005.1527933
Zusammenfassung
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.
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Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 21. Aug. 2005 - 21. Aug. 2005, Guangzhou, China
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MORENT, Dominik, David PATTERSON, Michael R. BERTHOLD, 2005. Towards context-aware similarity metrics (invited paper). Proceedings of 2005 International Conference on Machine Learning and Cybernetics. Guangzhou, China, 21. Aug. 2005 - 21. Aug. 2005. In: 2005 International Conference on Machine Learning and Cybernetics. IEEE, 2005, pp. 5596-5598 Vol. 9. ISBN 0-7803-9091-1. Available under: doi: 10.1109/ICMLC.2005.1527933BibTex
@inproceedings{Morent2005Towar-24304,
year={2005},
doi={10.1109/ICMLC.2005.1527933},
title={Towards context-aware similarity metrics (invited paper)},
isbn={0-7803-9091-1},
publisher={IEEE},
booktitle={2005 International Conference on Machine Learning and Cybernetics},
pages={5596--5598 Vol. 9},
author={Morent, Dominik and Patterson, David and Berthold, Michael R.}
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<dcterms:abstract xml:lang="eng">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.</dcterms:abstract>
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