August 21, 2006
Bartell results
First tried it with the target ground truth being the PPK kernel on uspop37. Did
pretty awfully on the R-precision task, about .16 (a random kernel with the correct diagonal gets about .125).
Using the LFM-collection ground truth and uspop1000, the results were much better. Below is a plot of R-precision vs. Bartlell's 'k' parameter, which is the dimensionality of the semantic space.
Also, the LFM ground truth kernel by itself gets very high R-precision: .567, max hubness 325.
Ah ha... But if I normalize the collections before computing the kernel, then the Bartell results are much better:
