Creating a data classification scheme for your data warehouse has many benefits for data security and governance, such as improved data protection, compliance, quality, and value.

Learn how data governance teams can ensure that data is properly classified and labeled, and what benefits they can gain from doing so.

Data classification, in the context of information security, is the classification of data based on its level of sensitivity and the impact to the university should that data be disclosed, altered, or ...

The generalization performance of SVM-type classifiers severely suffers from the `curse of dimensionality'. For some real world applications, the dimensionality of the measurement is sometimes ...

Appendix A, which provides a step-by-step procedure for classifying data according to this data classification scheme. Appendix B, which provides examples of data in each classification level.

Purpose This document defines the William & Mary system and data classification scheme and establishes procedures for protecting critical IT systems and sensitive and protected university data ...

We propose a scheme for pattern classifications in applications which include ambiguous data, that is, where pattern occupy overlapping areas in the feature space. Such situations frequently occur ...

A data classification standard being drafted by Canadian banks will make it easier for third-party service providers to protect regulated data. A similar effort is needed in the U.S., experts say ...

Identification, classification and handling of Purdue data, classified as public, sensitive or restricted, is essential to ensure the appropriate protection is applied.

In order to create a custom text classification model, you will need quality data to train it. This article covers how you should select and prepare your data, along with defining a schema. Defining ...