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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: Using Item Based recommenders as content based recommenders
Date Thu, 23 Jul 2009 18:28:57 GMT
This can work just fine.

Basically, you are precomputing the results of a similar document search.
Naive implementation of similar document search can be relatively slow, but
it can be sped up dramatically by simply using a filter to pull the most
interesting terms out of a document before doing the search.

Once you do that, then it doesn't make a lot of sense to do the searches
ahead of time, especially if you cache the results of the real-time search.

On Thu, Jul 23, 2009 at 10:41 AM, Claudia Grieco <grieco@crmpa.unisa.it>wrote:

> Item-based recommenders can be initialized with pre-computed item-item
> similarities, right? And what if those item similarities are computed using
> a Content Based technique (example off the top of my head, Cosine distance
> between the text of two documents computed using Lucene)? Am I missing
> something?
>



-- 
Ted Dunning, CTO
DeepDyve

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