A study of various NLP methods for multilabel classification over a sample dataset of movies and their genres. Approaches include Bag of Words, Word2Vec, and Bag of Concepts (a combination of BoW and W2V). Bag of Concepts has been inspired by this paper and its implementation.
Each approach has used various classification techniques and compared using F1 score as metric. Note that the training dataset has discrepencies and as such, the proposed methods might not fully illustrate their capabilities.