imgSeek and related projects blog

The Flickr Suggestions demo had been offline for the past weeks but should be now online.

Basic user recommendation is now available on the “Users” tab.

Recommendation algorithms available:

• By tag frequency for photo contributions of each user: what the system does is score each other user on the database based on the number of tags you have in common. Each user is represented internally as a sparse vector with tags as dimensions, where the value on each of these dimensions equal the number of Flickr contributed photos that contain that tag. A vector product is then made with each other user in order to find the most similar one. Several different metrics may be used to tell how similar each user is.
• More to come !

We have around 1.8mi user-tag tuples on the database so a recommendation takes about 6 seconds, which is really not good since server CPU usage stays at 100% during this time. This is going to improve soon as I work around better indexing and scoring techniques.

Completely hidden from users is an A/B test for determining recommendation algorithm variants that work better. Feedback provided by users are stored together with parameters chosen randomly for each generated recommendation.

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Rough draft on features to come:

• Improved content-based image searching:
  • External image (by upload or URL) suppport for similarity search
  • Sketch applet for searching for similar images
• Image recommendation based on:
  • currently favorited photos (by visual similarity or tags)
  • contacts
• Contact recommendation based on:
  • contacts in common
  • currently favorited photos (by visual similarity or tags)
• < your suggestion here ! >

It has actually been online for a few weeks already as I’ve ironed out some bugs and added new features.

Current features are: Searching for visually similar images within a given set of tags or from the entire database, which consists of roughly 25k images from the “interesting” pool.

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