Doorbell

The barrier between you and your best resume is only ever a click of a button.

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Inspiration

We have all gone through the struggle of trying to perfect a resume. You spend all day reviewing it, staring at this one sheet of paper, but it never seems to be perfect. Never fear! Doorbell is here to meet your resume review needs.

What it does

Simply upload your resume and Doorbell will check for common resume errors, such as period mistake, incorrect capitalization, misspellings, and incorrect verb tense. Additionally, our unique key word technology will search the web for job postings in your field, find common key words, and cross check your resume against these key words. If your resume is missing any important key words, we will notify you to ensure that your resume does not fall through the cracks.

How we built it

Doorbell is built with Vue.js for the front-end and Flask for the back-end. The resume parsing algorithm is written in Python. We utilize the Google Cloud Platform Natural Language API for part of speech tagging and verb tense detection. We then utilize the Microsoft Azure Bing Spell Check API for spell checking and the Microsoft Azure Text Analytics API for key word search.

Challenges we ran into

Formatting the data in such a way that it can be easily passed between the front end and the back end was a challenge. Resumes are often in either Word Document or PDF forms, which are both difficult to parse. Furthermore, we had difficulty deciding on a back-end architecture that best fit our needs.

Accomplishments that we're proud of

We are proud of our innovative keyword search, our comprehensive grammar and consistency check, and our clean, easy to use UI.

What we learned

Before this Hackathon, no one on our team had any full stack experience. We learned how to connect a front end to a back-end through a Rest API. We also learned how to modify a Word Document through Python libraries.

What's next for Doorbell

We want to expand the functionality of Doorbell to include more robust key word search, such as location specific job posting key words. We also want to accommodate for a wider range of file types.

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