Authorship clustering using multi-headed recurrent neural networks

Understand

A recurrent neural network that has been trained to separately model the language of several documents by unknown authors is used to measure similarity between the documents.

• It is able to find clues of common authorship even when the documents are very short and about disparate topics.
• While it is easy to make statistically significant predictions regarding authorship, it is difficult to group documents into definite clusters with high accuracy.