A1 – Recommendation System

In assignment 1 you shall implement a recommendation system for the movies data set in any programming language you like. You can work alone or in group of two students. You shall present your application and code at an oral examination.

Grade Requirements
  • Build a recommendation system that can find similar users and find recommendations for
    a user, using the movies large dataset (see Datasets page)
  • You can verify that your application works by using the example dataset from the lecture (can also be downloaded at the Datasets page)
  • Implement the recommendation system using a RESTful web service as back-end, and a browser client GUI as front-end
  • Use Euclidean distance as similarity measure
  • Implement the Pearson Correlation similarity measure
  • It shall be possible to select which measure to use from the web application
  • Implement functionality for pre-generating an Item-Based Collaborative Filtering table by
    transforming the original data set
  • Use the pre-generated table to implement a second way of finding recommendations for
    a user
  • It shall be possible to select how to find recommendations from the web application
    (Item-Based or User-Based)

Welcome to CoursePress

en utav Linnéuniversitets lärplattformar. Som inloggad student kan du kommunicera, hålla koll på dina kurser och mycket mer. Du som är gäst kan nå de flesta kurser och dess innehåll utan att logga in.

Läs mer lärplattformar vid Linnéuniversitetet

Student account

To log in you need a student account at Linnaeus University.

Read more about collecting your account

Log in LNU