Overview on NLP Techniques for Content-Based Recommender Systems for Books
Melania Berbatova · 2019
Recommender systems are an essential part of today's largest websites.Without them, it would be hard for users to find the right products and content.One of the most popular methods for recommendations is contentbased filtering.It relies on analysing product metadata, a great part of which is textual data.Despite their frequent use, there is still no standard procedure for developing and evaluating content-based recommenders.In this paper, we first examine current approaches for designing, training and evaluating recommender systems based on textual data for books recommendations for the GoodReads website.We examine critically existing methods and suggest how natural language techniques could be employed for the improvement of content-based recommenders.