How can I implement a recommendation engine?

Question

Please be patient with my writing, as my English is not proficient.

As a programmer, I wanna learn about the algorithm, or the machine learning intelligence, that are im

Answer 1

The are 2 different types of recommendation engines.

The simplest is item-based ie "customers that bought product A also bought product B". This is easy to implement. Store a sparse symmetrical matrix nxn (where n is the number of items). Each element (m[a][b]) is the number of times anyone has bought item 'a' along with item 'b'.

The other is user-based. That is "people like you often like things like this". A possible solution to this problem is k-means clustering. ie construct a set of clusters where users of similar taste are placed in the same cluster and make suggestions based on users in the same cluster.

A better solution, but an even more complicated one is a technique called Restricted Boltzmann Machines. There's an introduction to them here