Trending items
trending recommendation model is used to highlight the trending (or in other workds, most popular) items in your application. But it's not just about sorting items by popularity!
Metarank can:
combine multiple types of interactions: you can mix clicks, likes and purchases with different weights.
time decay: clicks made yesterday are much more important than the clicks from the last months.
multiple configurations: trending over the last week, and bestsellers over the last year.
Configuration
A separate block in the models section:
the final item score combines click, like and purchase events
purchase has 3x more weight than click, like has 1.5x more weight than click
purchase has less agressive time decay
only the last 30 days of data are used for clicks and purchases, but 60 days are used for likes
Time decay and weight
The final score used to sort the items is defined by the following formula:
When multiple interaction types are defined, per-type scores are added together to get the final score.
Time decay configuration allows a granular control over the decaying. Here's a click importance is weighted for different decay values:
We recommend setting decay:
within a range of 0.8-0.95 for 1-month periods.
within a range of 0.95-0.99 for larger periods.
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