What else do people who have bought an item buy? what are the main points of implementation of this function?

1. for example, a bought item A and item B today. he placed the order and B recommended item B below when buying item. Or, a bought item A and placed an order today, and bought item B the next day. when B bought item A, item B is recommended below. Is this idea reasonable? What else do you know about this... 1. for example, if a Buys item A and item B today, he places the order, and item B is recommended below when B buys item.
Or, a bought item A and placed an order today, and bought item B the next day. when B bought item A, item B is recommended below.

Is this idea reasonable? What else do you need to think more deeply about this function?

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1. for example, a bought item A and item B today. he placed the order and B recommended item B below when buying item.
Or, a bought item A and placed an order today, and bought item B the next day. when B bought item A, item B is recommended below.

Is this idea reasonable? What else do you need to think more deeply about this function?

Mobile phone editing (+ _ +)

Analysis of a large number of user behaviors and suggestions are given again. this is a big data application. the key to big data applications lies in the statistical data, rather than the data of a person.

For this function, you can count the number of people who have bought A (recently) and what they have bought in the near period, by the number of people (or times, retrieve the first few.

Of course, this simple algorithm may not meet your actual needs. what do you actually need? you need to analyze it yourself and add some conditions, such as adding an item category, analysis of promotion activities and other factors