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From Otis Gospodnetic <>
Subject Re: Item-based Collaborative Filtering
Date Mon, 25 May 2009 01:15:56 GMT


This should more than get you going:

And half way down the page:

Sematext -- -- Lucene - Solr - Nutch

----- Original Message ----
> From: Nagu <>
> To:
> Sent: Sunday, May 24, 2009 7:48:51 PM
> Subject: Item-based Collaborative Filtering
> Hi,
> I need some guidance in implementing item-based Collaborative Filtering in
> Mahout.
> To give an example, I built a recommendation engine using python (and I
> don't know damn about programming in general) last year based on some real
> customer data from my company (e.g. customers who bought this stuff also
> bought these...). I have some SQL procedures that spits the data for the CF
> algorithm, and the python program crunches the dataset, and spits out the
> recommendations for each customer (up to 50 recommended items) and it saves
> recommendations in a database. I created a simple web framework using django
> to present the recommendations given a customer ID. So sales teams can go to
> an intranet page and get recommendations for any given customers. I update
> the whole recommendations output every 15 days.
> I want to produce something like this using Mahout just to get a feel of
> Mahout. It will be something like, take this customer purchase history, and
> run the item-based CF algorithm, give me the recommendations for a given
> customer and save it in a database for me.
> Where can I find some step by step implementation of some examples in
> Mahout. I want to understand how this whole thing works and I want to start
> tinkering with some real time data from the company where I work. I also
> want to build some abstraction into this machine learning so that I can use
> the output that comes out of Mahout and feed to internal business/customer
> process and apply some business logic on top of this to make the results
> more meaningful.
> I am not sure if I am asking for too much, but I think I definitely need
> some guidance.
> Thank you,
> Nagu

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