thank you for reading this post
I recently read an aritlce about using ElasticSearch as a Recommendation System. Now I'am trying to implement my own simple "Frequently buyed together" Recommender based on ElastisSearchs aggregations and an articleId as input.
A document in my dataset contains the following fields (I parsed a CSV file via logstash):
- orderId / articleId
So different than in the mentioned article my dataset is "flat". The documents in ElasticSearch are representing the purchase of a single article and not the whole "receipt". The connection to the "receipt" is made by the orderId.
I tried to use nested aggregations :
terms on orderId -> terms on articleId -> filter on a specific id ...
But now I'am kind of stuck. Do you think my dataset suits this task? Do you have any ideas how to help me?
Thank you very much!