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book_recommender's Introduction

Installazione

Per poter utilizzare il sistema è necessario andare ad installare le seguenti librerie:

  • Gensim
  • Flask
  • SciPy
  • Flask
  • Numpy

Contenuto del repository

  • Main.py: interfaccia del web service. Gli endpoint definiti sono

    • /SelectModel/id: gli id disponibili sono 1-7 per la selezione dei modelli

    • /getSuggestions: prende in input l'oggetto JSON con i seguenti campi :

       {
           movies
           entities
           movietoIgnore
           negativeEntity
           recListSize
       }
  • RSCCore.py: contiene le funzioni dei file che accedono alla Knowledge Base ed effettua i calcoli di similarità legati alle proprietà

  • Dataset: è presente il file books_info.csv dove sono presenti tutti i libri con annesse caratteristiche (trama, scrittore, subject, genere)

  • Model:ogni file identificato da nome_modello.py e seguono la stessa struttura. Inoltre, in ogni cartella devono essere presenti i file dei modelli già addestrati. Qualora non fossero presenti, i modelli saranno riaddestrati alla prima esecuzione del programma oppure sono scaricabili da https://drive.google.com/file/d/1gbbMt6ZeOd8yK5PFrR_9iAtWFfaVzHHS/view?usp=sharing

book_recommender's People

Contributors

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