Inspiration
The inspiration for Recommendify sprang from the desire to merge browsing experiences with personalized music, enhancing online engagement and creating an immersive atmosphere for users.
What it does
Recommendify, a Chrome extension, intuitively gauges the tone of the website you're on and tailors music recommendations accordingly. It enhances browsing by creating personalized playlists that match the vibe of each webpage. It does this by finding keywords on webpages and sends those keywords to Spotifys API for curated music recommendations.
How we built it
We crafted Recommendify using a blend of HTML, python, and CSS, leveraging machine learning APIs for sentiment analysis. The extension integrates seamlessly with Chrome, ensuring a smooth user experience.
Challenges we ran into
Working with the Chrome extension framework was a challenge because it was new to us. There were limited resources online and limited documentation.
Accomplishments that we're proud of
Successfully implementing a prototype within the hackathon's timeframe stands out as a significant achievement. Additionally, fine-tuning the extension to deliver accurate music recommendations was a point of pride.
What we learned
How to make a chrome extension. How to query the Spotify API. How to use BeautifulSoup and the python Natural Language Toolkit to search for keywords on a page.
What's next for Recommendify
In the future, we would like to add client-side dynamic rendering. We also aim to refine Recommendify by expanding its compatibility to other browsers. Additionally, we plan to incorporate user feedback to enhance music recommendation accuracy and diversity, creating a more personalized experience for our users.
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