Custom Ranking
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Stream allows you to configure your own ranking method. You can add multiple ranking methods to a given Flat feed group.
An example ranking config is shown below:
Available Functions
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name | description |
---|---|
Basic Arithmetic | The following are supported: + - * / ( ) ^ |
ln(x) | Log Function natural base |
log(x) | Log Function base 10 |
sin(x) | Trigonometric sine function |
cos(x) | Trigonometric cosine function |
tan(x) | Trigonometric tangent function |
abs(x) | Absolute value |
min(a,b) | Minimum value |
max(a,b) | Maximum value |
trunc(x) | Truncates to the nearest integer value |
round(x) | Rounds to the nearest integer value |
decay_linear(t) | Linear Decay |
decay_exp(t) | Exponential Decay |
decay_gauss(t) | Gauss Decay |
rand_normal() | Returns a normally distributed number in the range [-inf, +inf] with standard normal distribution (stddev = 1, mean = 0) |
rand_normal(a,b,σ,µ) | Returns a normally distributed number in the range [a, b] with specific normal distribution (stddev = σ, mean = µ) |
rand() | Returns a random number in the range [0, 1.0) |
rand(a,b) | Returns a random number in the range [a, b) |
to_unix_timestamp(t) | Converts a time value to a unix timestamp |
Adding Activities
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Below is an example of how to add activities with custom ranking:
Retrieving Activities
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Below is an example of how to retrieve activities sorted by custom ranking:
Configuring ranking can be complex. Feel free to reach out to support if you have questions.
More visibility into ranking variables
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If you need to inspect your ranking variables at runtime this can be achieved like so
Decay & Ranking
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Stream supports a Linear, Exponential, and Gauss decay. For each decay function, we support 4 arguments: Origin, Scale, Offset, and Decay. You can pass either a timedelta string (such as 3d, 4w), or a numeric value.

Parameters
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name | description | default |
---|---|---|
origin | The best possible value. If the value is equal to the origin the decay function will return 1. | now |
scale | Determines how quickly the score drops from 1.0 to the decay value. If the scale is set to "3d" the score will be equal to the decay value after 3 days. | 5d |
offset | Values below the offset will start to receive a lower score. | 0 |
decay | The score that a value at scale distance from the origin should receive. | 0.5 |
direction | left, right or both. If right is specified only apply the decay for the right part of the graph. | both |
The example below defines a simple_gauss with the following params:
scale: 5 days
offset: 1 day
decay: 0.3 day
This means that an activity younger than 1 day (the offset) will return a score of 1. An activity that is exactly 6 days old (offset + scale) will get a score of 0.3 (the decay factor). The full JSON config is shown below:
You can specify defaults for the variables you use. The example above sets popularity to 1 if it's missing from the activity. We highly recommend setting up defaults to prevent errors when retrieving activities without these variables.
Configuring ranking can be complex. Feel free to reach out to support if you have questions!
Analytics & Reaction Counts
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In this example, we define defaults for activities that might be missing any analytics or reactions on it. Then, a linear combination of these numbers is adjusted according to passed time.
Call time custom parameters
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The scoring algorithm is working off of data such as parameters on the activity itself, analytics counters or reaction counters. For most use cases this is enough to present a relevant ranked feed based on those (semi-static) parameters, but it's lacking the capabilities to rank a feed based on a users own preferences.
In order to rank a feed based on a users preferences (i.e a personalized feed) Stream now accepts custom parameters that can be used at call time in the scoring algorithm.
Example: Music service
Consider the example of a music service that lets users upload songs and that they have a "global" front page feed that highlights the latest uploaded songs (activities). A naive approach might be to leave it unranked (i.e ranked by time) but this might not be front page worthy content. A better approach could be to rank the activities in this feed by the number of views or reactions on the activity, like a "new and hot" feed. The best approach is potentially to have a "new and hot" feed that also takes into account the type of activities (i.e type of music) that the user likes.
Consider two different users "the metalhead", which only listens to metal and "the classicist", which only listens classical music. Lets say we have this list of recent activities posted to the "global" feed.
We can then score these activities with the following scoring algorithm:
score = w_rock*classes.rock + w_pop*classes.pop + w_metal*classes.metal + w_classical*classes.classical + w_rap*classes.rap
and at call time we can supply the weights for a specific user, i.e for "the metalhead" we can specify the weights as
{"w_rock": 5, "w_pop": 1, "w_metal": 20, "w_classical": 4, "w_rap": 0}
which will put song4 and song1 at the top of the feed for that user. "The classicist" only cares about classical music with these weights
{"w_rock": 0, "w_pop": 0, "w_metal": 0, "w_classical": 1, "w_rap": 0}
which will order the feed based on the classical score only so song6 and song5 will be at the top of the feed for that user.