Diversification

diversity
Computes how different your current ranking item is compared to other items within the same ranking. Numeric and string fields are supported.
Diversification over numeric fields
Consider that all items in your inventory have a numeric price field:
{
  "event": "item",
  "id": "81f46c34-a4bb-469c-8708-f8127cd67d27",
  "item": "item1",
  "timestamp": "1599391467000",
  "fields": [{"name": "price", "value": 69.0}]
}
Then for a ranking below:
{
  "event": "ranking",
  "id": "81f46c34-a4bb-469c-8708-f8127cd67d27",
  "timestamp": "1599391467000",
  "user": "user1",
  "session": "session1",
  "items": [
    {"id": "item1"},
    {"id": "item2"},
    {"id": "item3"} 
  ]
}
we can compute how different each item price compared to the median price across the whole ranking with the following configuration snippet:
- name: price_diff
  type: diversity
  source: item.price # only item.* fields are accepted
  ttl: 90d # optional, when to expire tracked fields
  top: 10 # optional, take only top-N items to compute the median
For example, given the following item prices:
p1: price=100
p2: price=200
p3: price=250
p4: price=300
p5: price=220
So for a ranking [p1, p2, p3, p4, p5] we compute a median value of 220, and then compute the difference:
p1: price_diff=-120
p2: price_diff=-20
p3: price_diff=30
p4: price_diff=80
p5: price_diff=0
When you have a very long ranking, it's worth to consider limiting the amount of items taken into account, when computing median. When setting top=3, for the same set of items in the ranking event above, you'll get the median of 200:
p1: price_diff=-100
p2: price_diff=0
p3: price_diff=50
p4: price_diff=100
p5: price_diff=20
Diversification over string fields
This type of diversification can be useful to see how different your items over low-cardinality fields like tags, colors, sizes and categories. Both string and string[] field types are supported.
When all your inventory items have a field color like in an example below:
{
  "event": "item",
  "id": "81f46c34-a4bb-469c-8708-f8127cd67d27",
  "item": "item1",
  "timestamp": "1599391467000",
  "fields": [{"name": "color", "value": "red"}]
}
Then for a ranking below:
{
  "event": "ranking",
  "id": "81f46c34-a4bb-469c-8708-f8127cd67d27",
  "timestamp": "1599391467000",
  "user": "user1",
  "session": "session1",
  "items": [
    {"id": "item1"},
    {"id": "item2"},
    {"id": "item3"} 
  ]
}
we can compute how frequently each color is presented in the result set with the following configuration snippet:
- name: color_diff
  type: diversity
  source: item.color # only item.* fields are accepted
  ttl: 90d # optional, when to expire tracked fields
  top: 10 # optional, take only top-N items to compute the histogram
The difference algorithm builds tag frequencies over the ranking (so color -> count in our example above), and then computes relative intersection between tags of item and tag frequencies. An example:
given a frequency of {red: 50%, green: 30%, blue: 20%}
for an item having only red color, the score will be 50%.
for a red-blue item, the score will be 50%+20%=70%
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