We all have our own personal interests and sometimes, news feeds don't show us what we want to see. We want to save your time and only show you relevant news whether it's about health, technology or politics. University students often get caught up in their academics and neglect global news so we want to close that gap of knowledge with our web application, News Flash.

What it does

News Flash uses machine learning to recognize, model and predict what you're going to search for next based on your search history. As a user, you would prompt the website by speaking to it directly. For example, if you want to get an update about the technology world you could say: "Tell me about the latest technology." Our program would parse through what you say and pick out the key words; in this case it would be 'technology.' We would then increment your total count for technology so the next time you ask for general news, it would give you more articles about technology.

How we built it

In order to build a working web application in under 24 hours, we used several APIs such as Google Speech, News Databases as well as Firebase to store the information we collect. The interface was coded using HTML and CSS and the rest was created using JavaScript and node.js.

Challenges we ran into

Initially, News Flash was intended to first run on Amazon Echo, then later designated to be a Chrome Extension. However, due to time constraints, the design was changed to be a web application. In addition, we used technology and languages that we have little experience with.

Accomplishments that we're proud of

What we learned

A greater understanding on how to build Google Chrome Extensions, their corresponding APIs, and framework was established. Increased familiarity with JavaScript, HTML, and Firebase.

What's next for News Flash

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