> A quick test would be to consider two clicks to be required as a measure of
> interest.  My guess is that your data will suddenly become too sparse to
> use.

Can you quantify this? Lets say a recommender system has n users and m
items. Is it possible con conclude, how much data (ratings) you need
to run recommendations? Are there any rough estimations for judging
the sparsity of the data?



2010/7/28 Ted Dunning <[email protected]>:
> On Wed, Jul 28, 2010 at 12:53 PM, Simon Reavely 
> <[email protected]>wrote:
>
>> However, since I have no idea how significant extra clicks are I think this
>> is a good one to start with.
>>
>
> To 0-th order, they aren't. :-)
>
>
>>
>> With more work I'll try to evaluate the quality of that measure (number of
>> clicks) and look for others that could be better indications of preference.
>>
>
> A quick test would be to consider two clicks to be required as a measure of
> interest.  My guess is that your data will suddenly become too sparse to
> use.
>



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