GenoQuest

model

Inspiration

Facebook is a hub of connecting people from whole world.Why depend on random friend suggestions offered by facebook search your genomic friends having similar traits as you by physique,intelligence,Big Five traits,social habits.Also Family search offers loads of family relation links. Syncing the family data and find your most similar family member.

What it does

It collaborates facebook,genomic data from genomic link and optionally family search data and generate friends suggestions for facebook and family matches for family search.The app is a chrome extension when authenticated with the above dependencies fetches data and correlate to populate list of people nearer to your traits.

How I built it

Using facebook graph to get user details and log it with genomic link data of the user in Amazon Redshift via AWS S3 using AWS lambda.If user has family search account that data is also logged.Using some similarity ,correlation algorithms the data is comm-unitized and the people similar to users data are suggested as friends by providing their profile links.

Challenges I ran into

Accumulating vast data from various provides through a chrome extension,Logging data into Redshift,AWS lambda for processing the data.

Accomplishments that I'm proud of

To sync facebook and genomic data and form meaningful friendship suggestions.Using Redshift to log all data so to enhance the functionalities by mining it.

What I learned

Dealing with limitations of chrome extension,data handling and correlating

What's next for GenoQuest

Applying machine learning and other community detection algorithms to cluster users and support for add targeting,public event invitations,Groups,health aspects.