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Document Classification or Document Categorization is a process to assign different classes or categories to documents as required, eventually helping with storage, management, and analysis of the documents. It has become an important part of the computer sciences and the daily functioning of many companies today.

Documents may be classified ing to their subjects or ing to other attributes (such as document type, author, printing year etc.). In the rest of this article only subject classification is considered.

Some Examples of Text Classification: Sentiment Analysis. Language Detection. Fraud Profanity & Online Abuse Detection. Detecting Trends in Customer Feedback. Urgency Detection in Customer Support.

The PORTION MARKS establish the OVERALL CLASSIFICATION of the document. (S) There are three levels of classification ? TOP SECRET, SECRET, and CONFIDENTIAL. (S) There are two ways to classify a document ? ORIGINAL CLASSIFICATION or DERIVATIVE CLASSIFICATION.

Document classification can be used to moderate the content automatically. You can train machine learning models to classify documents into different categories, such as hate speech, profanity, NSFW, and more. Content classification can then be removed or flagged for review.

The United States government classifies sensitive information ing to the degree which the unauthorized disclosure would damage national security. The three primary levels of classification (from least to greatest) are Confidential, Secret, and Top Secret.

For example, if you were classifying clothing you might classify by color and put all green clothes into a category, with all red clothes in a separate category, and all blue clothes in a third. Your principle of classification would then be color.