Deep Learning for Natural Language Processing

4 Textual similarity

This chapter covers

• Representing data for authorship analysis with deep learning
• Applying classifiers to authorship attribution
• Understanding the merits of MLPs and CNNs for authorship attribution
• Verifying authorship with Siamese networks

One of the most common applications in natural language processing (NLP) is determining whether two texts are similar. Common applications include

• Document retrieval—Determining query-result similarity

• Topic labeling—Assigning a topic to an unlabeled text based on similarity with a set of labeled texts

• Authorship analysis—Determining whether a text is written by a certain author, based on texts attributed to that author

We will approach the topic of text similarity from the perspective ...