Exactly so. The weighting of events is done by the algorithm. To add biases
would very likely be wrong and result in worse results. It is therefore not
supported in the current code. There may be a place for this type of bias but
it would have to be done in conjunction with a cross-validation tests we have
in our MAP test suite and it is not yet supported. Best to leave them with the
default weighting in the CCO algorithm, which is based on the strength of
correlation with the conversion event, which I guess is purchase in your case.
On Nov 28, 2016, at 2:19 PM, Magnus Kragelund <m...@ida.dk> wrote:
It's my understanding that you cannot apply a bias to the event, such as "view"
or "purchase" at query time. How the engine is using your different events to
calculate score, is something that is in part defined by you and in part
defined during training.
In the engine.json config file you set an array of event names. The first event
in the array is considered a primary event, and will be the event that the
engine is trying to predict. The other events that you might specify is
secondary events, that the engine is allowed to take in to consideration, when
finding correlations to the primary event in your data set. If no correlation
is found for a given event, the event data is not taken into account when
Your array might look like this, when predicting purchases: ["purchase",
"initiated_payment", "view", "preview"]
If you use the special $set event to add metadata to your items, you can apply
a bias or filter on those metadata properties at query time.
From: Harsh Mathur <harshmathur.1...@gmail.com>
Sent: Monday, November 28, 2016 3:46:46 PM
Subject: Tuning of Recommendation Engine
I have successfully deployed the UR template.
Now I wanted to tune it a little bit, As of now I am sending 4 events,
purchase, view, initiated_payment and preview. Also our products have
categories, I am setting that as item properties.
Now, as I query say:
For both queries, I get the same number of recommendations just the score
varies. The boosting isn't changing any recommendations, just changing the
scores. Is there any way in UR that we can give more preference to some events,
it will help give us more room to try and see and make the recommendations more
relevant to us.
“Perseverance is the hard work you do after you get tired of doing the hard
work you already did."