Photoree

http://www.photoree.com/photos/tour

 The site describes itself as being "to photos what Last.fm is to music and StumbleUpon is to websites."  It is an image recommendation system that uses a thumbs up or thumbs down method of rating.  Preferences are recorded and used on the fly to recommend other images that the user might prefer.  The recommendations are user-to-user based and might cross some privacy boundaries if not careful.  The user is allowed to see the stats on how popular an image is.  It goes on to tell the user WHO liked or disliked the image.  There are security settings that the user can opt into to decide not to share their preferences to others.

***WARNING***

There are no guarantees that the images made available for rating or suggestion will not be nudity.

***WARNING***

Youtube Doppleganger

For three weeks now I have been rating youtube videos under to different accounts.  One account prefers to watch music videos and movie trailers while the other account prefers to watch stand up comedy and magic tricks. 

For both accounts ratings were done by adding the videos to the "Favorites" list and by using a 1 to 5 star system.  

Searching for 'comedy' and 'card tricks' in each account yields mostly the same results with roughly 10% difference.  'Comedy' yields the same results for both.  

The main page, channels, and 'video' section for each always shows the same items.  

The interesting thing is that the 'Promoted Videos' are different for each always.  

Youtube --bubbles

When watching a video on YouTube in full screen mode there is a button that appears next to the play button.  This button, which I'll call the bubbles button, reveals an interactive network of "related" videos.  I say "related" because they appear to related mostly by submitting user and popular vote.  The video that you are watching appears as a slightly larger bubble or node in the network in the center.  As the user mouses over the other bubbles, more bubbles appear.  Mousing over one bubble reveals all bubbles that are directly linked to that bubble.  The network plain is expandable in the X and Y directions.  

I still have found no evidence, other than popular vote, to show that the recommendations are at all personalized to the user.

For next week I'll set up another account and make very different 'favorites.'  Hopefully I'll be able to do the same search from each account and compare the results to see how personalized they are.

CarWale.com recommended that I get new interests in cars

Carwale.com

This recommendation system uses car attributes and car shopper needs and preferences to recommend cars.  I attempted to find something that matches what I want in my new car.  I had to try several times before it was able to give me something.  I ended up giving it very little information.  

The content based system "works" by collecting information on preferences through a series of check boxes, fill-in the blanks and fancy sliding values.  It then attempts to find a vehicle or vehicles that matches those values.  It does not ask questions that deal with your interests or hobbies.  The attributes are all specific to the cars themselves.

No special account is required to use the system... only special interests.

Link

YouTube -- YouRecommend???

I've begun looking into YouTube's "recommendation" system.  At first I'm quite confused about what is going on under the hood.  YouTube definitely has a content based system.  At the same time however it allows users to rate videos Netflix style.   It also allows users to declare something as a "Favorite."   It is unclear to me whether or not YouTube uses my ratings and favorites to "recommend" videos to me.  The Netflix style star system is being used for sorting.  Videos can be sorted into a 'Top Rated" category.  I have not found a system the appears to be using these ratings other than "Top Rated."  To test I began rating videos.  I rated mostly music video, trailers, and videos of Santa Claus falling of the roof.  I hoped to sway any possible recommendation system towards videos similar to them.  Once I returned to the main page I found that I was being should videos of "Super Tuesday."  This either means that not enough input has been given, no system is in place using the stars, or the JUNO soundtrack is closely related to Barrack O'Bama.

GoogleTechTalks on WikiLens - User generated recommendation data

A talk by Dan Frankowski on BEER!  More spefically Frankowski talks about WikiLens.org, a site which allows users to start their own recommendation systems on any topic including beer.  This system works similar to a wiki but does require some level of user rating before changes are allowed to be made.  Like a wiki, users can start a new topic or add content to an existing topic.  The goals of project are to allow users to FIND, ADD, create DEEP CHANGE, MICRO-CONTRIBUTE, and SEE OTHERS. 

FIND: Members should be able to find items that interest them

ADD: Members should be able to add items immediately

DEEP CHANGE: Members should be able to uniquely identify items, and define and redefine their attributes and organization

MICRO-CONTRIBUTE: Members should be able to make small contributions

SEE OTHERS: Members should be able to see each other and their contributions

Frankowski is  software engineer for Google Groups and his paper is called "Recommenders Everywhere."

The video: (~35 minutes)

http://www.youtube.com/watch?v=bsgLSb9Dbz8

The slides:

http://www.cs.umn.edu/~dfrankow/files/wikilens12.ppt

Microsoft's Behavioral Recommender System's Patent

http://www.google.com/patents?id=XVh4AAAAEBAJ&dq=recommendation+systems

View patent at USPTO (will require a special plug-in)

Filing date: Jul 15, 2003
Issue date: Mar 14, 2006
Inventor: Christopher B. Weare

Claim Summary:

This system is unique from attribute based or collaborative filtering based systems in that it recalculates to make predictions based on current behavior of the user.  Users rate items and rate the recommendations made by the system.  This is still similar to Netflix to me.

I have not been able to determine *exactly* where MS is using this.  It is possible that has been shelved.