We often find ourselves struggling to read through boring articles (for school or for pleasure). We think, why can't there just be a tl;dr (too long;didn't read) summary at the end of every article that we read. We wanted to make that happen, so SherlockSummary was born.
What it does
SherlockSummary takes an article URL and uses IBM Watson's Bluemix AlchemyAPI to analyze it. The output is a combination of the article's key concepts, emotions of the authors, and keywords.
How we built it
We used Heroku for the back end and used HTML/CSS for the front-end. We implemented AlchemyAPI to scan the article given for concepts, emotions, and other criteria.
Challenges we ran into
We struggled with learning Node.js as well as implementing Bluemix's AlchemyAPI.
Accomplishments that we're proud of
We're proud of creating a web application that integrates a lot of moving parts (AlchemyAPI, Bluemix, and Heroku).
What we learned
What's next for SherlockSummary
We hope to continue to clean up the user interface and add support for more of Alchemy Language's features. We might even explore using Bluemix's Language Translator to translate articles then determine their content and emotion.