I'm very happy to hear that the problem of similar tastes is one that resonates with you.
We are working very hard to quickly add all the places in the US, so you can rate the ones you love! Please request these places by clicking the mail button in the bottom right corner of the app, and we will do our best to get them into the system promptly!
We will be building out more channels soon. You mentioned coworking spaces, what else would you like to see?
- Jeremy, VP of Product and Machine Learning at Ness Computing
Thanks for the feedback. We made a slightly different mechanism for rating on the personalize page (the list of places you saw when you first came to the app allowing you to quickly rate). Either a user can skip a place manually by clicking the X, or can scroll down to the bottom and skip all the places that you don't like. You are saying you would rather just scroll past the ones you don't know?
I work with the Machine Learning team at Ness. Thanks for all the feedback! Please email us at [email protected] as you have more thoughts, especially about where Ness does and does not work for you.
With regard to only teaching Ness by rating restaurants 4-5 stars, this is a great point, especially for the first 10 ratings. There are a couple particular ways we address this today:
1) Which restaurants you pick tells us a lot. Did you rate hole in the walls vs. expensive places? We have spent a lot of time working on our collaborative filter to address this. Wikipedia has a good article for a starting ground on this, and the papers that came out of the Netflix Prize are great [http://www.netflixprize.com/assets/GrandPrize2009_BPC_BellKo...].
2) On the personalize page, there are multiple stages. One of them is to confirm that the system is correct about places you don't like, which is obviously also very informative.
3) Sometimes, as with your Chipotle example, we won't be right. Telling us where we are wrong is particularly helpful in correcting the system, which in some sense gives us more information that confirming what we already know. Think of it of correcting a person, who misunderstood what you like from examples you gave. In a metaphorical sense, this is like providing results that have more entropy.
We are working very hard to quickly add all the places in the US, so you can rate the ones you love! Please request these places by clicking the mail button in the bottom right corner of the app, and we will do our best to get them into the system promptly!
We will be building out more channels soon. You mentioned coworking spaces, what else would you like to see?
- Jeremy, VP of Product and Machine Learning at Ness Computing