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From Sean Owen <sro...@gmail.com>
Subject Re: ItemBasedRecommender
Date Fri, 11 Dec 2009 10:13:37 GMT
You probably want a user-based recommender since you have very few
users, relatively. Performance should not be a problem given the size
of your input -- probably can compute recommendations in tens of
milliseconds.

You will need to use RecommenderEvaluator to find which of many
possible implementations produces the best results on your input. For
example, experiment with a nearest-n user neighborhood with small
values of n, and try Euclidean distance-based and log-likelihood-based
similarity metrics. Try several variations and see which produces the
lowest evaluation score.

On Fri, Dec 11, 2009 at 6:43 AM, F.Ozgur Catak <f.ozgur.catak@gmail.com> wrote:
> approx. 100.000 rows and 2000 users
>
> On Fri, Dec 11, 2009 at 2:25 AM, Sean Owen <srowen@gmail.com> wrote:
>
>> The best algorithm really depends on your data.
>>
>> How many items and how many users do you have? that will determine
>> which algorithms will perform better.
>>
>> Which algorithms will produce the best recommendations is hard to
>> tell. Usually you have to use RecommenderEvaluator with lots of
>> implementations and your data to find which seems to work best.
>>
>> if you can say more about your data, maybe I can guess about the best
>> implementations to try.
>>
>> On Thu, Dec 10, 2009 at 9:56 PM, F.Ozgur Catak <f.ozgur.catak@gmail.com>
>> wrote:
>> > Hi again,
>> >
>> > Finally I understand the item similarity :). In our b2b project we need
>> to
>> > develop a recommendation system. I want to use mahout. Is there any best
>> > practice. And also another question, is mahout enogh mature to use our
>> > production enviroment.
>> >
>> > thanks
>> >
>> > On Thu, Dec 10, 2009 at 9:31 PM, Sean Owen <srowen@gmail.com> wrote:
>> >
>> >> No, the similarity metric is passed in as an ItemSimilarity metric.
>> >> There is no implementation based on a model, if that's what you mean.
>> >> What else?
>> >>
>> >> On Thu, Dec 10, 2009 at 7:27 PM, F.Ozgur Catak <f.ozgur.catak@gmail.com
>> >
>> >> wrote:
>> >> > Yes, I read the javadoc but i need the algorithms. For example, does
>> >> > recommandation system uses apriori algorithm to find similar values?
>> etc.
>> >> >
>> >> > Maybe it is mine problem, because I'm also a newbi about data mining.
>> >> >
>> >> > Thanks
>> >> >
>> >>
>> >
>>
>

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