PV254 Project

Project for PV254 Recommender Systems on FI MUNI.

Team:

• Lenka Horváthová
• Lucie Kurečková
• Markéta Vítková

Setup

• Clone this GIT repository:

      $ git clone https://github.com/lenkahorvathova/pv254-project.git
  

• Set PYTHONPATH variable:

      $ cd pv254-project
      $ export PYTHONPATH=`pwd`
  

• Download review data and metadata files of Toys & Games from Amazon Product Data Website into data folder:

      $ mkdir data
      ...
      $ ls data
          meta_Toys_and_Games.json.gz     reviews_Toys_and_Games_5.json.gz
  

• Create and activate Python environment:

      $ python3 -m venv venv
      $ source venv/bin/activate (Mac)
      $ source venv\Scripts\activate (Windows)
  

  • to deactivate Python environment: $ deactivate

• Install requirements:

      $ pip install -r requirements.txt 
  

• Set up and populate a database (~ 9 min):

      $ python3 scripts/setup_db.py --review_file "data/reviews_Toys_and_Games_5.json.gz" --meta_file "data/meta_Toys_and_Games.json.gz"
  

• Check data in the database:

  • connect to DB: $ sqlite3 data/amazon_product_data.db
  • list tables in DB: > .tables
  • view a schema of a table: > .schema <table>
  • a query example: > SELECT * FROM review LIMIT 10;
  • exit sqlite3 program: > .quit

• Set FLASK_APP variable:

      $ export FLASK_APP=frontend/server.py
  

• Run the application locally and go to 'http://127.0.0.1:5000/':

      $ python3 frontend/server.py
  

Directory and File Structure

    pv254-project/
    └─── data/
    |   |   amazon_product_data.db
    │   │   meta_Toys_and_Games.json.gz
    │   │   reviews_Toys_and_Games_5.json.gz
    |   
    └─── frontend/
    |   └─── static/
    |   └─── templates/
    |   |
    |   |   server.py
    |
    └─── scripts/
    |   │   setup_db.py
    |   |   ...
    │   
    └─── venv/
    |
    │   README.md
    |   requirements.txt
    │   schema.sql

Citation

R. He, J. McAuley. Modeling the visual evolution of fashion trends with one-class collaborative filtering. WWW, 2016 J. McAuley, C. Targett, J. Shi, A. van den Hengel. Image-based recommendations on styles and substitutes. SIGIR, 2015