Item2Vec-based Approach to a Recommender System
Name
Vitali Kuzmin
Abstract
The aim of this thesis was to develop a vector space representation model for a recommender system. The model implementation was based on the method called Item2Vec; this approach was chosen because recent studies have shown that it displays competitive results. The work consists of implementing the approach, evaluating it on test data and deploying it into production in the Software Technology and Applications Competence Center. Evaluation results show that the implemented model is indeed competitive and is suitable for building recommender systems.
Graduation Thesis language
English
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Carlos Bentes, Mark FiĊĦel
Defence year
2017