In this chapter, we discuss the application of transfer learning to text document categorization. Text categorization is a very popular natural language processing task. The key objective is to assign a document to one or more classes or categories based on its textual content. This has widespread applications in the industry including email classification to spam/non-spam, review and ratings classification, sentiment analysis, email or incident routing where we categorize emails\incidents so that it can be automatically assigned to respective person. The following are the major topics that will be covered in this chapter:
- Text categorization in general, industry applications, and challenges
- Benchmark text categorization datasets and performance of traditional models
- Word representation by dense vectors—deep learning models
- CNN document model...
