Text Document Classification

During the last twenty years the number of text documents in digital form has grown enormously in size. As a consequence, it is of great practical importance to be able to automatically organize and classify documents. Research into text classification aims to partition unstructured sets of documents into groups that describe the contents of the documents. There are two main variants of text classification: text clustering and text categorization. The former is concerned with finding a latent group structure in the set of documents, while the latter (also known as text classification) can be seen as the task of structuring the repository of documents according to a group structure that is known in advance.