"Interestingness" function for StackExchange questions I am trying to put together a data-mining package for StackExchange sites and in particular, I am stuck in trying to determine the "most interesting" questions. I would like to use the question score, but remove the bias due to the number of views, but I don't know how to approach this rigorously.
In the ideal world, I could sort the questions by calculating $\frac{v}{n}$, where $v$ is the votes total and $n$ is the number of views. After all it would measure the percentage of people that upvote the question, minus the percentage of people that downvote the question.
Unfortunately, the voting pattern is much more complicated. Votes tend to "plateau" to a certain level and this has the effect of drastically underestimating wildly popular questions. In practice, a question with 1 view and 1 upvote would certainly score and be sorted higher than any other question with 10,000 views, but less than 10,000 votes.
I am currently using $\frac{v}{\log{n}+1}$ as an empirical formula, but I would like to be precise. How can I approach this problem with mathematical rigorousness?
In order to address some of the comments, I'll try to restate the problem in a better way:
Let's say I have a question with $v_0$ votes total and $n_0$ views. I would like to be able to estimate what votes total $v_1$ is most likely when the views reach $n_1$.
In this way I could simply choose a nominal value for $n_1$ and order all the question according to the expected $v_1$ total.

I've created two queries on the SO datadump to show better the effect I am talking about:
Average Views by Score
Result:

Average Score by Views (100-views buckets)
Result:


The two formulas compared 
Results, not sure if straighter is better: ($\frac{v}{n}$ in blue, $\frac{v}{log{n}+1}$ in red)

 A: One might define an interesting question as one that has received comparatively many votes given the number of views. To this end, you can create a baseline curve that reflects the expected number of votes given the views. Curves that attracted a lot more votes than the baseline were considered particularly interesting.
To construct the baseline, you may want to calculate the median number of votes per 100-view bin. In addition, you could calculate the median absolute deviation (MAD) as a robust measure for the standard deviation per bin. Then, "interestingness" can be calculated as 
interestingness(votes,views) = (votes-baselineVotes(views))/baselineMAD(views) 

A: This is my theory. I think there are two kinds of questions: those that remain mostly within SE (which usually have fewer views), and those that are viewed by outsiders because it was linked from somewhere else (usually have more views). 
For the questions that remain mostly within SE, votes are a good measure of interesting questions. This is the point of votes.
When a question is linked to outside the site the votes stop meaning as much. Some linking sites may have very few SE members, others may have more. The variance of the number of votes for these questions is probably high (as evidenced by your score vs view plot, where the right side of the curve blooms out). These questions will have more views, and views MAY be a better indicator of interesting questions. Or questions that a larger community happened to find more interesting. There are many variables in this situation, and I think it would be worth trying to find more information to differentiate these cases. Does SE publicize referral information? 
