On 27.11.2011 Nishant Chandra wrote: > I want to identify rules such as: after acquiring product 1 and then > product 3, customers have an increased likelihood > (75%) of purchasing product 4 next.
What is your goal with discovering these rules? Assuming what you want is implementing a feature that recommends items to customers they are likely to buy: Did you check the fpgrowth implementation already? Though it does not cover the temporal aspect you mention it might still be of value for you as it is capable of discovering items that are typically puchased together. If you would rather personalize your offerings to the preferences of each of your customers you might be better of taking a closer look at the collaborative filtering implementations of Mahout. Isabel
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