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reviews-parser's Introduction

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PURPOSE

This our final project in BMSTU.

AUTHORS

  1. Smyslov Maxim (Back-end)
  2. Bogdanova Valeria (Front-end)

ARCHITECTURE

image

TECHNOLOGIES

This app works as a web service, which parses marketplaces, then classifies comments as negative or positive and finaly sends the results in Telegram bot

Technology stack:

  • Telebot
  • Flask
  • Aiohttp
  • TF-IDF as text transformer
  • XGBoost as tonality classifier
  • mongoengine as ORM
  • MongoDB on parser side
  • PostgreSQL on bot side

DATASET

For classification was taken a dataset of human labeled comments from marketplaces. This dataset contains comments from cat food products and each comment is marked as positive or negative.

MODEL QUALITY

Precicion = 0.9260379462934971
Recall = 0.9390572924932551
Roc auc = 0.9466007732268533

HOW TO RUN

  1. Fill in the credentials in the .env file (there is an example)
  2. docker-compose build
  3. docker-compose up
  4. Enjoy

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