Inspiration

Our inspiration was our passion for the business side of technology; where will future technology bring us? How can we look at previous trends to predict future ones? The TrendE team knows the importance of good technology, which we start now.

What it does

The algorithm takes any input (technology, tech business trend, product, etc.) and suggests 5 of the statistically most accurate relative trends to the input, accompanied by the percentage of which they are the hottest trend in the market.

How we built it

We began developing the core algorithm by stripping useful keywords from the target's Wikipedia page. These keywords were then searched again on Wikipedia, where their forecast information was acquired and ranked based on its community-wide relevancy and frequency of edits.

Challenges we ran into

A major challenge was understanding the HTML breakdown of Wikipedia and acquiring exactly the most relevant keywords to the target, hereby stripping the junk. Another challenge was determining a scoring system for each trend and comparing them.

Accomplishments that we're proud of

Getting used to APIs (unfortunately we were API n00bs coming into YHack!), as well as getting the front-end progress bar (this was actually tricky).

What we learned

Pinging the internet for data can be a hassle, especially with 1000+ people using the same connection!

What's next for TrendE

The implementation of social media data to strengthen the algorithm's confidence in its top 5 relevant results

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