Mining Association rules from a data warehouse and a transactional database [on hold]












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I wonder if it is possible to perform market basket analysis to extract the association rules from a data warehouse and a transactional database in the same time to predict the future purchases of a specific user?










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put on hold as too broad by Esmailian, Ethan, Mark.F, Sean Owen yesterday


Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.


















  • $begingroup$
    I mean by using historical data from a data warehouse and a transactional database, can we extract the valuable association rules to make a personalized content for a user. for example: if a user bought a pc, in 2 years, he would likely buy a pc battery. [focusing on TIME dimension]
    $endgroup$
    – Geek Girl
    yesterday


















1












$begingroup$


I wonder if it is possible to perform market basket analysis to extract the association rules from a data warehouse and a transactional database in the same time to predict the future purchases of a specific user?










share|improve this question







New contributor




Geek Girl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$



put on hold as too broad by Esmailian, Ethan, Mark.F, Sean Owen yesterday


Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.


















  • $begingroup$
    I mean by using historical data from a data warehouse and a transactional database, can we extract the valuable association rules to make a personalized content for a user. for example: if a user bought a pc, in 2 years, he would likely buy a pc battery. [focusing on TIME dimension]
    $endgroup$
    – Geek Girl
    yesterday
















1












1








1





$begingroup$


I wonder if it is possible to perform market basket analysis to extract the association rules from a data warehouse and a transactional database in the same time to predict the future purchases of a specific user?










share|improve this question







New contributor




Geek Girl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$




I wonder if it is possible to perform market basket analysis to extract the association rules from a data warehouse and a transactional database in the same time to predict the future purchases of a specific user?







machine-learning data-mining recommender-system association-rules market-basket-analysis






share|improve this question







New contributor




Geek Girl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











share|improve this question







New contributor




Geek Girl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|improve this question




share|improve this question






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Geek Girl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









asked 2 days ago









Geek GirlGeek Girl

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New contributor




Geek Girl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.





New contributor





Geek Girl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






Geek Girl is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.




put on hold as too broad by Esmailian, Ethan, Mark.F, Sean Owen yesterday


Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.









put on hold as too broad by Esmailian, Ethan, Mark.F, Sean Owen yesterday


Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.














  • $begingroup$
    I mean by using historical data from a data warehouse and a transactional database, can we extract the valuable association rules to make a personalized content for a user. for example: if a user bought a pc, in 2 years, he would likely buy a pc battery. [focusing on TIME dimension]
    $endgroup$
    – Geek Girl
    yesterday




















  • $begingroup$
    I mean by using historical data from a data warehouse and a transactional database, can we extract the valuable association rules to make a personalized content for a user. for example: if a user bought a pc, in 2 years, he would likely buy a pc battery. [focusing on TIME dimension]
    $endgroup$
    – Geek Girl
    yesterday


















$begingroup$
I mean by using historical data from a data warehouse and a transactional database, can we extract the valuable association rules to make a personalized content for a user. for example: if a user bought a pc, in 2 years, he would likely buy a pc battery. [focusing on TIME dimension]
$endgroup$
– Geek Girl
yesterday






$begingroup$
I mean by using historical data from a data warehouse and a transactional database, can we extract the valuable association rules to make a personalized content for a user. for example: if a user bought a pc, in 2 years, he would likely buy a pc battery. [focusing on TIME dimension]
$endgroup$
– Geek Girl
yesterday












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