In this session we will show how to build a meetup.com recommendation engine using Neo4j and Python. Our solution will be a hybrid approach which makes uses of both content based and collaborative filtering using Neo4j to glue all the data together, Cypher to query the dataset and Python to do analysis and pre/post processing of data.
In this session we will show how to build a meetup.com recommendation engine using Neo4j and Python.
Our solution will be a hybrid which makes uses of both content based and collaborative filtering to come up with multi layered recommendations that take different datasets into account e.g. we'll combine data from the meetup.com and twitter APIs.
We'll evolve the solution from scratch and look at the decisions we make along the way in terms of modelling and coming up with factors that might lead to better recommendations for the end user.