distl provides the client with a “distilled” version of articles as they browse the web. The client has to do very little - distl automatically extracts relevant text from a webpage and gives back a summarized version with sentiment analysis.

HTML/CSS/JS Frontend:

• Beautifully designed
• Filters out ads from relevant article text
• Sends text to backend
• Recieves and displays summarized text and sentiment analysis
• Sends user ratings on text analysis to backend

Node.js Backend:

• Recieves source text from frontend and caches it
• Performs text summarization using a Node.js plugin
• Sends text to Google Natural Language API for sentiment analysis
• Aggregates results and sends analysis back to frontend
• Recieves user rating on analysis and sends the cached sourced text to Google Storage

Google Cloud Platform:

• Hosts the Node.js backend using Google App Engine
• A VM created by Google Compute Engine uses CRON to schedule PySpark jobs on a Google Hadoop cluster
• Spark apps analyze a day's worth of source text and user ratings (stored in Google Storage) for patterns (i.e. most frequently visited site, number of of dislike v.s. likes for a particular site, etc.)