Yes, that is correct. Collection 'features' stores mapping between features
and their scores.
For simplicity, I tried to keep the level of detail about these collections
to a minimum.
Both collections contain thousands of records and are updated by (lily)
hbase-indexer. Therefore storing scores/we
Accordingly to what I understood the feature weight is present in your second
collection.
You should express the feature weight in the model resource ( not even in
the original collection)
Is actually necessary for the feature weight to be in a separate Solr
collection ?
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Al
Thanks, Alessandro, for your reply.
Indeed, LTR looks like what I need.
However, all of the LRT examples that I have found use a single collection
as a data source.
My data spans across two collections. Does LTR support this somehow or
should I 'denormalise' the data and merge both collections?
M
Hi Ginsul,
let's try to wrap it up :
1) you have an item win N binary features ( given the fact that you
represent the document with a list of feature Ids ( and no values) I would
assume that it means that when the feature is in the list, it has a value of
1 for the item
2) you want to score (or
Hi,
I have two collections. The first collection 'items' stores associations
between items and their features. The second collection 'features' stores
importance score for each feature.
items: item_id- one-to-many - feature_id
features: feature_id - one-to-one - importance_score_int
The
