Content Recommendation Steps

concepts –> setup server –> logging –> configure data –> realtime activity –> offline model –> runtime configuration –> microservices –> recommendations

Offline Recommendation Model Creation

Seldon provides a variety of item recommendation models that can be created and makes it easy for new custom models to be added.

The current integrated models are:

Confguration is either passed on the command line to the offline jobs or set in zookeeper.

Offline Data Store

The Seldon modelling and data manipulation jobs assume a structure for the data storage. This structure allows easy integration into a production environment where models are created periodically, usually each day. The directory structure is of the form


e.g. for a matrix_factorization model created for client client1 on 27 Jan 2014 (unix epoch day 16461) would be


You can use a network file store, AWS S3 or soon HDFS for the actual store.

The jobs that require activity data will use a start day and a number of days to collect from the filesystem the data they need. They will gather data from folders of the form:


For example:


The output path will be of the form:


For example:



Configuration is held in zookeeper as JSON in nodes of the form:


For example:


All jobs usually have a set of basic parameters they need including

An example:

  "startDay" : 1,
  "days" : 1,