  Although a lot of research has been done on utilising Online Social Media
during disasters, there exists no system for a specific task that is critical
in a post-disaster scenario -- identifying resource-needs and
resource-availabilities in the disaster-affected region, coupled with their
subsequent matching. To this end, we present NARMADA, a semi-automated platform
which leverages the crowd-sourced information from social media posts for
assisting post-disaster relief coordination efforts. The system employs Natural
Language Processing and Information Retrieval techniques for identifying
resource-needs and resource-availabilities from microblogs, extracting
resources from the posts, and also matching the needs to suitable
availabilities. The system is thus capable of facilitating the judicious
management of resources during post-disaster relief operations.
