Exactly so. Recording different types of input was one reason to build a site 
that looked good enough to feasibly get a little traffic.

For instance, one of the recommendation types is “Based on videos you recently 
viewed” You see these on detail pages as well as the recommend page. These 
detail pages views are put in log files but also recorded in realtime for 
queries. The recently viewed videos are used as a query on the 
similarity/indicator matrix. This yields somewhat weak results IMO, partly 
because of the mismatch in actions. You are trying to recommend from the “liked 
videos” indicator matrix using “viewed detail page” actions. This is a case for 
the cross-recommender but I don’t have enough detail views yet to calculate a 
cross-indicator matrix so I make do with the one I have.

The analogy of a shopping cart recommender might be the watchlist on the site. 
A user’s watchlist indicates an item-set that interests the user. Once enough 
of these are collected Solr will quite easily allow for queries against 
everyone’s watchlists using the user’s watchlist as the query. Not as strong as 
buying things together in a shopping cart but still may be of value. When you 
go to your watchlist page (not really implmented yet) you’d see other videos 
from similar watchlists. This type of query could be combined with the 
watchlist as a query on the liked-video indicator matrix to give better 
results. 

Other actions are also possible to use like search terms. An indicator matrix 
of search terms and videos clicked could be blended with fultext search to get 
personalized search results—again given enough usage.

The site is equipped to gather all of this data if there is enough traffic.

On Apr 6, 2014, at 10:33 PM, Ted Dunning <[email protected]> wrote:

On Mon, Apr 7, 2014 at 5:18 AM, Pat Ferrel <[email protected]> wrote:

> Combining this kind of metadata with CF data has been important to the big
> guys but elusive to the rest of us. And a recommender that seamlessly
> integrates the different methods is rare. Solr + Mahout does it better than
> anything I’ve seen on the OSS or pay software market.
> 

Combining with meta-data is a huge deal.

Frankly, having many kinds of indicators in the index so that you can mix
and match is big as well (maybe half as big).  This lets you tune the
weight of different kinds of input.

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