The Apache Mahout Recommender Documentation mentions the following:
I'm not sure how the actual construction is done in the above line. Can someone provide an example?
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This example refers to the case where you have the similarities already computed, by the Hadoop job for example, and stored on the filesystem or database . As the constructor documentation reads:
If you have tens of millions of recommendations or less, you can simply compute similarities on the fly and use the other
For example:
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There's no magic here, it's just suggesting you create a bunch of those ItemItemSimilarity objects, one for each item-item similarity that you know about.
You can make it this way or any other way you want. |