vionwinnie / tableTennis-product-review

Comparative Table Tennis product review

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Comparative Product Reviews on Table Tennis Rubbers

Purpose

  • Our team implements natural language processing models to mine comparative opinions on table tennis products

Tech Stack

  • MongoDB, Sqlite3, Python, Flask, Dash, Plotly, Fastapi, CSS, Bootstrap, Heroku

Live Deployment

Directory Structure:

  • |-- EDA: Folders contain data analysis jupyter notebook
  • |-- scraper: webscraping/data ETL module
  • |-- comparison: Roberta classification model training using labelled data and inferencing on unlabelled data
  • |-- information_retrieval: Extracting Entity, Attribute, Directions from comparative sentences
  • |-- common: common utils (connect to db, data query)
  • |-- viz: wordcloud visualization
  • |-- frontend: dashboard

Create Local Testing Environment

  • conda create -n ds4a-t15 python=3.7 pip
  • conda activate ds4a-t15
  • pip install -r requirements.txt

Fire up Local Front End Environment

Fire up local sqlite db

  • cd frontend/plotly/db
  • sqlite3
  • sqlite> .open tableTennisData.db

Contributors

  • Charlotte Giang
  • Eyan Yeung
  • Pooja Umathe
  • Jessie Zhang
  • Winnie Yeung (Team Lead)

Further Reading

About

Comparative Table Tennis product review

License:MIT License


Languages

Language:Jupyter Notebook 99.7%Language:Python 0.3%Language:CSS 0.0%