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https://issues.apache.org/jira/browse/BIGTOP-1271?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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jay vyas updated BIGTOP-1271:
-----------------------------

    Affects Version/s: backlog

> BigPetStore: Embed user "types" into the generated data.
> --------------------------------------------------------
>
>                 Key: BIGTOP-1271
>                 URL: https://issues.apache.org/jira/browse/BIGTOP-1271
>             Project: Bigtop
>          Issue Type: New Feature
>          Components: Blueprints
>    Affects Versions: backlog
>            Reporter: jay vyas
>
> The data set generation in BigPetStore results in data with temporal and 
> geographic patterns, however, there are no "personal" biases in the data.
> We need to add personal biases into the data so that the Mahout recommender 
> is capable of teasing out statistically significant product clusters for 
> users. 
> A simple implementation:  
> {noformat} 
> given 2 "types" of customers (i.e. dog people, cat people)
> t = hash (customer_name) % 2
> if(t==0)
>    customer buys only dog products
> if(t==1) 
>    customer buys only cat products
> {noformat}
> This approach will easily scale and consistently embed profiles into each 
> persons purchases.  Obviously using some OO magic we can create customers who 
> also buy cat and dog products both... but the basic approach still remains 
> (hash code -> customer type -> product biases).



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