Abstract: Computing systems and methods for discovering new topics from digital documents are provided, including using a natural language neural network. Digital documents are processed using an encoder to obtain vectors, and the vectors are processed to form clusters. Topics are identified in association with each of the clusters. Based on the clusters, a word-topic matrix of probabilities of words detected in each topic is computed. A word-document matrix of probabilities of words detected in each one of the digital documents is also computed. A topic-document matrix of probabilities of each one of the plurality of topics in each one of the digital documents is then computed by factorizing the previous two matrices. This third matrix is then used to compute and output a topic distribution for each of the digital documents, which shows the topics generated by the computing system.