Using a value for a domain name determined by a machine learning engine

Abstract

A training set may be created to train a machine learning engine, such as an artificial neural network (ANN), to value a target domain name using data from previously sold domain names. The training set may comprise a plurality of word features vector of real numbers (information related to the words or tokens within the sold domain names), a plurality of word embedding vector of real numbers (word embedding of the words within the sold domain names), a plurality of context embedding vector of real numbers (sale context, i.e., location and date of a sale of a sold domain name), a plurality of DNS embedding vector of real number (DNS information of the sold domain name) and/or a plurality of domain name features vector of real numbers (data regarding the sold domain name). The ANN may then be trained on the training set, using the methods of gradient descent and back propagation, to value a target domain name.