SparQ - Next Gen Mobile Dating Application

Inspiration

What would it mean to you if you could find your perfect match without having to answer an endless survey, or swipe through hundreds of photos? Wouldn’t it be great if you could just tell your story, and be automatically matched with those who share a similar one?

What it does

Using a custom algorithm paired with Google’s Natural Language Processor running behind a React-developed app and the Google Cloud Platform, we are able to break down your story and match it with others’. Once you input your basic information, which is pulled from your Facebook login, you simply talk about yourself, what you like to do, your behaviors, how you spend your free time, etc. Then, SparQ automatically pulls up those who would be a good fit for you, making finding your ideal partner simpler and more natural.

How we built it

We starting with a thorough brainstorming process, looking at exactly how we'd want a user to interact with our dating app and how we can use our combined experience and/or external libraries and tools to be able to accomplish this. Then, we developed the codebase via divide-and-conquer, balancing working on code within our skillset and reaching out to try something new.

Challenges we ran into

It was extremely difficult to get different data types to parse correctly when they were going from a JSON file to a python script to another JSON file to being stored in MLAB to being handled by Google's App Engine to finally being sent to the end user. Furthermore, making our algorithm work and make sense so that we could really match users with the best fit was extremely difficult to figure out.

Accomplishments that we're proud of

For a team of three first-time Hackathoners, having no idea what we would do coming into the event, we actually were able to not only build from scratch a fully-working application—front-end, back-end, server, and database—but we also incorporated state-of-the-art technologies and languages to help us solve our problem, many of which we had never seen before.

What we learned

We learned a lot about node.js, general program management, how to use Google's cloud storage, how to use Google's MLAB, how to use Google's natural language processing, and how to interact between js and python files.

What's next for dating-app

Given more time, we would love to be able to implement more cool features, including:

Utilization of TensorFlow to adjust algorithm real-time based on user preferences Integration with Google login, Support for non-binary genders, Location-based preferences, In-app spell checker, and more!

Built With

• app-engine
• google-cloud
• google-natural-language-processing
• mlab
• mongodb
• node.js
• python