One of the things that has always confused me is how Flickr’s ‘interestingness’ score worked. It’s clearly not based directly on views — my most ‘interesting’ photos have ~500 views, while my most popular ones have ~5000. The same is true of comments, tags, groups, etc: Some of my most interesting photos are, all in all, the least obviously ‘popular’ ones.
However, reading through the patent on Interestingness, I see:
 The statistics engine generates statistics and other metrics based upon aggregated metadata. In one embodiment, the statistics engine determines the popularity of metadata (e.g., tags) within a grouping of media objects over a predetermined time period. For example, the statistics engine may determine the number of different users that have assigned a particular tag to one or more media objects within all groups on the system, within a single group, or within a set of media objects, over the last 24 hours. The aggregation engine may determine (and display) a histogram of the tags, and may determine the most frequently assigned tags (at any point in time or over a predetermined time period) by determining those tags either having a frequency exceeding a minimum threshold frequency or belonging to a predetermined number of the most popular tags.
The patent application doesn’t directly claim that this is used in the interestingness calculation, but this type of time-period based tag aggregation/valuation is clearly a non-obvious metric that can’t be calculated by looking directly at user-visible information on a single photo.
Still, none of this really changes the fact that I wish that flickr had a per-person ‘most interesting this week’ sort: my ‘eastern bunny’ photo above has been at the top of the interesting list for ages, and I want new interesting photos, damnit!