This is a nice course on Memory Based Reasoning in AI taught by Dr. Deepak Khemani and Dr. Sutanu Chakraborti at the Department of Computer Science & Engineering, Indian Institute of Technology Madras, Chennai, India. See
We have also included the new similarity measures proposed by Consonni & Todeschini (2012), and Todeschini, et al (2012).
Our Tutorial on Distance and Similarity was also updated, accordingly. Check it out at
Consonni, V. and Todeschini, R. (2012). New Similarity Coefficients for Binary Data. MATCH Commun. Math. Comput. Chem. 68, 581-592.
Todeschini, R., Consonni, V., Xiang, H., Holliday, J., Buscema, M., and Willet, P. (2012). Similarity Coefficients for Binary Chemoinformatics Data: Overview and Extended Comparison Using Simulated and Real Data Sets. J. Chem. Inf. Model. 52 (11).
The calculations presented in the new tutorial are so simple that can be carried out with a spreadsheet, online calculator, or by hand. Thus, the article is suitable for those interested in learning about vector space models, but that lack of a linear algebra background.
Another fast-track tutorial updated and improved is back!
This is a fast track tutorial on vector space calculations. A linear algebra approach is used. The tutorial covers term-document and term-query matrices, matrix transposition, dot products, cosine similarities, and local and global weights.