mahout-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Sebastian Schelter <ssc.o...@googlemail.com>
Subject Re: HELP for implicit data feed back - beginner
Date Fri, 22 Nov 2013 18:43:43 GMT
Hi Antony,

I would start with a simple approach: extract all customerID,itemID
tuples from the orders table and use them as your input data. How many
of those do you have? The datasize will dictate whether you need to
employ a distributed approach to recommendation mining or not.

--sebastian

On 22.11.2013 19:21, Antony Adopo wrote:
> Morning,
> 
> My name is Antony and I have a great recommender system to build
> 
> I'm totally new on recommender systems. After reading all scientific files,
> I didn't find relevant information to build mine.
> 
> ok, my problem:
> 
> I have to build a recommender systems for a retail industry which sold
> Building products
> 
>  I don't have Explicit data (ratings)
> 
> I have only data about purchases and all transactions and order and dates.
> as
> 
> Orders table
> 
> CustomerID
> Sales_ID
> Item_ID
> Dates
> Amount
> quantity
> channel_type (phone, mail,etc.)
> 
> 
> I have also specific informations about users
> 
> Users table
> CustomerID
> Group (engaged, frequent,buyer, newyer, etc.)
> 
> ... and product
> 
> Item_ID
> Item_name
> Iteem_parent (hierarchy)
> 
> I don't know how to use all these informations with mahout (or others tools
> or method) to do a good recommendation system (all presents are based on
> ratings and all mahout systems I have seen are also based on ratings or
> preference)
> 
> At beginning, I thought that I have to use classical datamining methods as
> Clustering or association rules but accurately recommanding n products
> between  2000 products  clustering in about 300 hierachical parents(not
> linked to domain) become difficult with classical data mining
> It is the reason that I turn myself to recommender system
> 
> 
> please Help
> thanks
> 


Mime
View raw message