Building a reciprocal recommendation system at scale from scratch: Learnings from one of Japan’s prominent dating applications

Online dating platforms have changed the paradigm of how people seek potential relationships. In this context, reciprocal recommendation systems consider the mutual ’match’ potential between users, i.e users who are likely to interact and potentially ’like’ each other. We present our experiences on how we devised algorithms to overcome data specific nuances, built and deployed the system from scratch in a relatively short time-span for one of the prominent dating applications in Japan.