Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Recommended Reading
Bunke H, Shearer K. A graph distance metric based on the maximal common subgraph. Pattern Recogn Lett. 1998;19(3):255–9.
Chang C-C, Lin C-J. LIBSVM: a library for support vector machines. 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
Dehaspe L, Toivonen H, King R. Finding frequent substructures in chemical compounds. In: Proceedings of the 4th International Conference on Knowledge Discovery and Data Mining; 1998. p. 30–6.
Deshpande M, Kuramochi M, Wale N, Karypis G. Frequent substructure-based approaches for classifying chemical compounds. IEEE Trans Knowl Data Eng. 2005;17(8):1036–50.
Fröhlich H, Wegner J, Sieker F, Zell A. Optimal assignment kernels for attributed molecular graphs. In: Proceedings of the 22nd International Conference on Machine Learning; 2005. p. 225–32.
Hansch C. A quantitative approach to biochemical structure-activity relationships. Acc Chem Res. 1969;2(8):232–9.
Kashima H, Tsuda K, Inokuchi A. Marginalized kernels between labeled graphs. In: Proceedings of the 20th International Conference on Machine Learning; 2003. p. 321–28.
Kramer S, Raedt L, Helma C. Molecular feature mining in HIV data. In: Proceedings of the 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 2001. p. 136–43.
Yan X, Yu PS, Han J. Graph indexing: a frequent structure-based approach. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2004. p. 335–46.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Yan, X. (2018). Mining of Chemical Data. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_1299
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1299
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering