While the popularity of continuous word embeddings has increased over the past years, detailed derivations and extensive explanations of these methods lack in the academic literature. This paper elaborates on three popular word embedding meth- ods; GloVe and two versions of word2vec: continuous skip-gram and continuous bag-of-words. This research aims to enhance our understanding of both the founda- tion and extensions of these methods. In addition, this research addresses instability of the methods with respect to the hyperparameters. An example in a food menu context is used to illustrate the application of these word embedding techniques in quantitative marketing. For this specic case, the GloVe method performs best according to external expert evaluation. Nevertheless, the fact that GloVe performs best is not generalizable to other domains or data sets due to the instability of the models and the evaluation procedure

Additional Metadata
Keywords Keywords: word embedding, word2vec, GloVe, quantitative marketing, food
Thesis Advisor Velden, M. van de
Persistent URL hdl.handle.net/2105/47697
Series Econometrie
Verstegen, G.J.A. (2019, July 23). dish2vec: A Comparison of Word Embedding Methods in an Unsupervised Setting. Econometrie. Retrieved from http://hdl.handle.net/2105/47697