Quotes Recommender

Project for course PV254 Recommender Systems. Web application for recommending quotes

The aim of this project is to implement recommendation algorithms. Database of quotes was obtained from https://www.brainyquote.com. Web app is implemented in Ruby on Rails.

Contributors

• Vojtech Hlavka
  • Data analysis
  • Data filtering
  • Evaluation
  • Charts and graphs
• David Luptak
  • Implementation of web app
    • Complete web app skeleton
    • Deployment on public domain
    • User interface
    • Authentication
  • Implementation of recommendation algorithms
  • Final presentation
• Martin Styk
  • Download of quotes database by scraping website www.brainyquote.com
  • Implementation of recommendation algorithms
  • Implementation of web app
    • Integration of recommendation algorithms
  • Final presentation

Project structure

Project has well known Ruby on Rails app structure.

Controllers

Controllers which handle HTTP requests are located inside app/controllers directory.

Controllers important for recommendations

• ratings_controller - method update is triggered when user enters a rating for a quote. It handles insert of new rating or change of existing rating. update method triggers methods adjust_user_category_preference, adjust_user_quote_length_preference, adjust_user_word_length_preference. These methods update user's profile everytime user rates a quote. This is the place where user's profile is built.

• home_controller - method index is triggered everytime when user wants to see a new quote. It parses request params and triggers quote selection algorithms on line 12. Category parameter is only used on first random quote selection. For all other quotes line 12 is executed.

Interactors

Interactors which are important for recommendations, located in app/interactors directory.

• initialize_quote - this interactor is triggered from home_controller. It delegates recommendation work to recommend_quote interactor.

• recommend_quote - chooses the recommendation algorithm based on user which invoked the method.

Services

Recommendation logic is implemented in service classes located in app/services directory. This is a list of all recommender services, you can find additional comments directly in source code classes.

• recommender_service - super class of all recommender service classes. It defines method show_next which is called by class clients. Method choose_next_quote is meant to be overriden by subclasses and returns the quote which should be shown.

• anonymous_recommender_service - service is used when user is not logged in. We don't know user's profile, so random quote is returned and entry about user activity on site is not saved.

• random_recommender_service - Method choose_next_quote returns random quote.

• score_board_recommender_service - base class for all advanced recommenders - global_popularity_recommender_service and classes based on its child learning_score_board_recommender_service, which compute score board (quote -> score - suitability for user). It overrides choose_next_quote method of recommender_service. Inside this method, abstract method compute_score_board is triggered. This method is meant to be overriden by subclasses. It should return result - scoreboard of quotes ordered and normalized. Top results are then shuffled in method score_board_recommender_service#choose_next_quote. Please see comments directly in the score_board_recommender_service class.

• global_popularity_recommender_service - extends score_board_recommender_service and overrides method compute_score_board to compute score of quotes based on their global popularity.

• learning_score_board_recommender_service - slightly changes behaviour of score_board_recommender_service - if user has seen less then 5 quotes, it returns random quote. All other logic is delegated to it's predecessor score_board_recommender_service. This is parent class for content_based_category_recommender_service, content_based_quote_analysis_recommender_service, content_based_mixed_recommender_service.

• content_based_category_recommender_service - computes scoreboard of quotes based on user's profile for categories. See comments in the source file.

• content_based_quote_analysis_recommender_service - computes scoreboard of quotes based on user's profile for text style. See comments in the source file.

• content_based_mixed_recommender_service - combines content_based_category_recommender_service and content_based_quote_analysis_recommender_service. It merges scoreboards computed by these services. Category has priority with 80% in final score, while text style has only 20%.

List of other important files

• Database schema - db/schema.rb

• Script for quotes download - scripts/quotes_finder.rb

• Quotes data (original and filtered) - data directory

Execution & development

Environment preparation

In order to set up your environment please follow the instructions provided here. It contains these main steps:

• Install required dependencies
• (Optionally) Install rbenv
• Install ruby (official documentation)
• Install rails and bundler (or other useful gems)

Development

• cd to the root directory of the project
• Run bundle install to install missing gems
• Run rails db:migrate to initialize the database schema
• Run rails db:seed to insert data into the database
• Run rails server >> http://localhost:3000/

Setup

Admin

To initialize an admin user in the system, run the following:

• cd to the root directory of the project
• Run rails console to start console for rails
• Create a user and add an admin role:

> user = User.new
> user.email = 'admin@admin.admin'
> user.password = 'adminadmin'
> user.add_role :admin
> user.save
# Because _user_ default role is assigned after create
> user.remove_role :user

• You are done. (You can leave the console by pressing Ctrl^D)

Google authentication

Exporting the following environment variables is needed to use Google authentication

GOOGLE_CLIENT_ID = <your client ID>
GOOGLE_CLIENT_SECRET = <your client secret>.

Facebook authentication

Exporting the following environment variables is needed to use Facebook authentication

APP_ID = <your application ID>
APP_SECRET <your application secret>