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I am studying the article at the following link,

Which applies Monte Carlo analysis to a decryption problem. The math is admittedly over my head at this point but I believe I understand the basics.

The goal is to compute a 'plausibility' (scalar) value, I think, that represents how close a decoded message is to making sense in English. The benchmark is defined by a 2-dimensional matrix that represents the frequency that characters occur together in a string of english language.

Is there a method using the dot-product of two matrices that produces a measurement of similarity between those two matrices on a scale of 0 - 1?

(The relevant function is on the first page of the pdf I linked).


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up vote 1 down vote accepted

So in the equation there, $M$ is a 26x26 (say) matrix. For letters $\ell_1$ and $\ell_2$, $M(\ell_1, \ell_2)$ is the conditional probability that the next letter is going to be $\ell_2$ given that the current letter is $\ell_1$. For instance:

We take a book, and count the number of times the letter 'e' occurs in that book -- say 15,000. Then we count the number of times the next letter is 'f' -- say, 200. With this in hand, we put

$M(\text{'e'}, \text{'f'}) = 200/15000 = 1.33%$.

Now the plausibility score,

$\text{Pl}(f) = \Pi_i M(f(s_i), f(s_{i+1}))$,

is just the associated probability of picking $f(s)$ among all possible strings of text of that length, based on our model that says that the only thing that influences what letter appears at a particular position is the letter before it. So it's nothing as complicated as you were imagining.

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I don't see how this answers the question, which, as I understand it, is about similarity measures between matrices. – joriki Sep 14 '11 at 5:54
This helps alot, though, thanks. I'm not sure I completely grasped the function initially. – Sean Thoman Sep 14 '11 at 5:59
@Sean: In what status does that leave your question? Do you still want to know about similarity measures? – joriki Sep 14 '11 at 6:30
@Joriki: His question was about an equation in the linked paper, which initially appeared to be making implicit use of a matrix similarity measure. As it turned out, this wasn't the case -- what appeared to be a family of matrices was actually notation for a particular entry of a single, fixed matrix, so the "matrix" in question was really a scalar all along. – Daniel McLaury Sep 14 '11 at 6:42
@user3296: I see. Thanks for the explanation. Since he accepted your answer, I presume you understood the problem better than I did. – joriki Sep 14 '11 at 6:55

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