We all have invites to so many networking events. It is not possible to attend all. We came up with InterestNet as a solution to explore interest demographics of the event. Wouldn't it be good to know what people with what interest and technological expertise are attending the event.
What it does
It takes in your LinkedIn handle while you register for an event. It scrapes the data from your LinkedIn profile and populates into a graph database. Then the information is aggregated and displayed according to the interest groups. It also shows the people who are closest match to you based on your professional interests.
How I built it
We build a Java scraper which crawls a given LinkedIn profile and extract the professional information like academic areas, skills and technologies. It then sends it to Neo4j database instance. The graph database populates the data and explores the relationships using cypher. UI is a web dashboard which shows all the aggregated information, clicking on which one gets a list of people in the interest group. Also there is a feature to find the people who match the best with you and what skill set they share with you
Challenges I ran into
Integrating the different technologies into a single solution. We have Java scraper, python wrapper for Neo4j and UI runs on Ruby with Sinatra
Accomplishments that I'm proud of
Putting the whole solution together in 24 hours. And taking advantage of people with different technical backgrounds.
What I learned
Team work, meeting deadlines, changing design plans according to deadlines
What's next for InterestNet
To be able to integrate with Event registration sites and be able to communicate with similar interest people