I was trying to listen to classical Indian fusion on YouTube today and found a certain limitation during this process. Compared to Pandora (which is music recommendation service like lastfm) listening to songs on YouTube is limited. I don’t have the option of starting my own station and relax and listen.
The prime difference between YouTube and Pandora would be the limited number/expressiveness of tags that YouTube videos have or which are being currently used. For instance a classical song on YouTube is often tagged as just ‘music’ or ‘entertainment’ w/o any regards to it’s musical or video content. On the other hand Pandora has pretty descriptive tags for it’s songs, which makes it easy to find songs in same genre even though these songs might not have the same artist or usual features like name-viewers. Moreover during a small glance I also observed that the options/suggestions that YouTube provides, while viewing a video, have a similar name/viewers, than content based features like classical, rock, or other.
Thus in future it will be interesting to see if Google could use these noisy tags in an intelligent way so that a user can use YouTube depending on his preference. Thus one one day I can use it as Pandora that recommends music based on similar content or like the current YouTube. Google has also been doing some related work here, one of which I came through was published in ICCV’11 by Thomas Leung and others on using weakly supervised learning for handling noisy labels/tags (noise is other source of nuisance). Another homework that I should do is read about the recommendation system that Google used and if they are doing something similar to those employed by online retail sites that use algorithms like latent models, matrix factorization etc (mostly unsupervised). I will revisit this discussion in future.