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Project Description.md

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Senior Design Project Idea

Members:

  1. Ben Hollar ([email protected]), Computer Science
  2. Erin Graska ([email protected]), Computer Science
  3. Stephanie Tam ([email protected]), Computer Science

Faculty Advisor:

  1. Dr. Chia Han ([email protected])

Final Abstract

Finding and collecting recipes can be a daunting task, and many online recipe sources distract users with unnecessary blogs or advertisements. The Spice Rack aims to reduce that problem by providing a web application where users can store their recipes without distractions and import recipes from online sources using a machine-learning driven content extraction process.

Detailed Description

The Spice Rack is a web-application dedicated to allowing users to import and collect their recipes in a central, persistent, and accessible hub. Key to enabling this was the implementation of a machine-learning (ML) backed algorithm that can, given a URL, automatically collect recipe information and populate our web forms without any user intervention. As such, the project was divided into 3 distinct pieces, worked on independently by one team member each, then combined to produce our final result. Those three pieces were:

  1. (Ben Hollar) Machine-learning recipe parsing, leveraging dragnet for content extraction and BERT for text classification.
  2. (Erin Graska) Backend web development, leveraging the Django web-development framework for Python
  3. (Stephanie Tam) Frontend web development and design, leveraging Django, HTML, and CSS to create an effective UI

When combined, these pieces form a complete web application, backed by a database which serves data via a REST API, and can ingest data using ML models -- fulfilling our original project goals.