We released this a couple of weeks ago, but we have new stuff to report.
In the Starbucks Saturation calculator that we built to show graphically how many Starbucks locations are close by, we did additional homework and came up with some interesting things. For example, did you know that the city farthest from a Starbucks is Adak, Alaska, and it is 1,044 miles away from the closest Starbucks? But for folks in Santa Fe Springs, California, there are 560 different Starbucks locations within only 25 miles. You can read our full report here (and don’t forget to Digg us if you like it!)
We did another update to the recommended places list. It should be a little faster, but it is still a bit slow. It’s really doing quite a lot of work, so please bear with us as we squeeze every CPU cycle to get it faster.
While we were working on this we thought that people might like to know who has similar tastes as they do, and perhaps even where those people are located (just to the city, this doesn’t actually show maps to exact address). The map below are the people I’m similar to, you can find this on the left hand side when you sign in, “Who am I similar to?”
These are people who when compared to your ratings, they are more similar than just the national average. As we get more ratings we will make it more and … Read More »
When we started Foodio54 we used the recommendation system that we developed during our attempt to win the NetFlix Prize. This works well on a data set which has a large amount of ratings data (like Netlix or Group Lens), but currently we don’t have enough ratings for this to be useful for us right now. So we needed a way to shrink the datapool, while at the same time increasing the number ratings (without any manipulation of the actual data). Impossible you ask? Not quite We think we have something which might even be better than the predictions we were doing for Netflix, especially on a sparely rated data set.
This still isn’t 100% perfect (even the Pre-Cogs in the movie Minority Report disagreed from time to time), but it should be really good. For some users we still … Read More »
We were recently featured on Mashable and they had some suggestions for us which we are working on.
Be able to subscribe to a user’s reviews
Add photos to reviews
Wishlist of places you’d like to eat
Add a personal recommendation system
These are all really great ideas, and in fact the restaurant review RSS feeds are now available (just after we read the Mashable post). You can now get a feed for one user or just one feed for all of your friends. We’ve been looking at ways to incorporate images with the restaurants for a while, and I think we will have another look to see how best we can accomplish this.
We have a wishlist feature, but in order to add something you need to have rated it, which in retrospect doesn’t make sense. Look for this in the next few days…maybe tomorrow … Read More »
We have a new spotlight feature available, a Starbucks Coverage Calculator. Sure people make jokes about how many Starbucks locations are around, but just how many of them are there? With this tool you can see how your location compares to your state and the country.
Topping the list was Santa Fe Springs, California, while there were some towns like Antelope, Montana don’t have a Starbucks for 100 miles.
We are pleased to report that we now accept OpenIDs. The OpenID Project allows you to have 1 username and password that you can take with you from site to site instead of having to remember multiple logins for each one. You get a url like http://you.myopenid.com and then you can use that URL to sign into sites which accept OpenID. For existing members, you can still log in as normal, we will soon be enabling you to assign an OpenID to an existing username. If you are interested in getting an OpenID, check out MyOpenId.com (it’s free, just like Foodio54). This is not something to expect from your bank or credit cards any time soon, but for most sites this makes signing in extremely easy.
We added the ability to sort search results by distance, rating (the national average), or alphabetically by restaurant name. Also on Friday we will release the first of a new series of features that are just fun ways to look at all of the data we are collecting. We think it’s done, but everytime I say that I find something wrong with it One more solid day of testing should be enough to release it for everyone.