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Date: Tue, 22 Jan 2013 20:50:18 +0100
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Subject: Re: Question - Mahout Taste - User-Based Recommendations...
From: Henning Kuich <hkuich@gmail.com>
To: user@mahout.apache.org
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Oh, I forgot one thing: Is it just as simple using the User-based
recommendation to find similar products, or is this only possible using
item-based recommendations? So basically if a given user rated a certain
product with x stars, to figure out what item is most like the one he has
just rated, but using only user-based recommendation algorithms?

HK


On Tue, Jan 22, 2013 at 7:44 PM, Henning Kuich <hkuich@gmail.com> wrote:

> That's what i though. I just wanted to make sure!
>
> Thanks so much for the quick reply!
>
> HK
>
>
>
> On Tue, Jan 22, 2013 at 7:40 PM, Sean Owen <srowen@gmail.com> wrote:
>
>> Yes that's right. Look as UserBasedRecommender.mostSimilarUserIDs(),
>> and Recommender.estimatePreference(). These do what you are interested
>> in, and yes they are easy since they are just steps in the
>> recommendation process anyway.
>>
>> On Tue, Jan 22, 2013 at 6:38 PM, Henning Kuich <hkuich@gmail.com> wrote:
>> > Dear All,
>> >
>> > I am wondering if I understand the User-based recommendation algorithm
>> > correctly.
>> >
>> > I need to be able to answer the following questions, given users and
>> > ratings:
>> >
>> > 1) Which users are "closest" to a given user
>> > and
>> > 2) given a user and a product, predict the preference for the product
>> >
>> > apart from the standard "return topN" recommendations. But as I
>> understand
>> > it, the above two questions are just "subquestions" of the topN problem,
>> > correct? Because the algorithm determines the "closest users" since
>> it's a
>> > user-based recommender, and since it calculates all potential user-item
>> > associations, the second question should also be taken care of.
>> >
>> > Do I understand this correctly?
>> >
>> > I would greatly appreciate any help,
>> >
>> > Henning
>> >
>> >
>> >
>> >
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>
>
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