"People you may know" recommendation to build a strong social network
One of our clients wanted to build a recommendation engine using well known big data tools. The primary idea is that if two people have mutual friends, then the system should recommend that they should connect with each other.
The recommendation engine is a part of their inhouse portal where professionals connect to each other based on their common interests, geographical locations.
The primary business requirement was to develop a system which recommends the friends(“ people you may know ”).
There were multiple challenges while developing the solution like,
Collecting real-time stream of data arriving at rapid speed.
Providing fault tolerant indexing solution for the recommendation engine.
Deliver accurate recommendations within limited time.
If two people have a lot of mutual friends, then the system should recommend that they connect with each other.
Our assumption is that friendship is bi-directional: if A is a friend of B, then B is a friend of A. We provided the solution by writing streaming jobs program which provides friends recommendations.
We also developed recommender system which performs the processing on user history and also provides the different recommendations based on user interests, events and user’s geographical location.
This type of solution is mostly used by prominent social and professional networking websites. By using our solution the users are able to,
We have followed sprint based application development for delivering the solution which includes various phases like,
Business requirements analysis.
Setup environment and application deployment.
We delivered a simple solution to our client organization and as a result the client organization users were able to,
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