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From Sebastian Schelter <sebastian.schel...@zalando.de>
Subject Re: Extracting association rules
Date Wed, 14 Apr 2010 15:46:09 GMT
Hi Sebastian,

I can only help you with what
GenericItemBasedRecommender.mostSimilarItems() does. It's basically what
you know from amazon.com: "People who like this item also like the
following items". Mathematically spoken, you have a matrix of the
preferences of users towards items and mostSimilarItems() searches the
highest ranking item vectors using some similarity function (usually
cosine or pearson correlation).

A good overview about how item-based collaborative filtering works and
what the most similar items are can be found in this paper (helped me
understand the whole issue):
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.144.9927&rep=rep1&type=pdf

Regards,
Sebastian

Sebastian Feher schrieb:
> Hi All,
>
> I'm looking at extracting association rules with Mahout. If I understand it correctly,
both GenericItemBasedRecommender.mostSimilarItems() and Parallel FP-Growth seem to provide
support for doing that. Is this true? If not what are the major differences between the two
(including scalability, performance)? Thanks.
>
> Sebastian


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