Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Automatic Message Classification

Published

Author(s)

Arthur Griesser

Abstract

Rising automation means fewer humans, maintaining more equipment, which is exchanging more information. This information torrent is expected to increase even further, with the implementation of advanced process control and new information transfer standards such as Interface A and Interface C. The information deluge will make it difficult to pinpoint the information necessary for resolve problems. Sooner or later automated support for problem diagnosis will become valuable. Data classifiers(such as neural networks and Bayesian filters) typically require features extracted from the classified data. They are also typically trained: the classifier is provided with example data, and their categories. The selection of categories and samples for training is something of an art: under-training and over-training can easily result in poor classification. This presentation considers classification without training or domain knowledge.
Proceedings Title
AEC/APC Symposium XVIII
Conference Dates
September 30-October 5, 2006
Conference Location
Westminster, CO

Keywords

Classification, Clustering, Pattern Recognition, Machine Learning

Citation

Griesser, A. (2006), Automatic Message Classification, AEC/APC Symposium XVIII, Westminster, CO (Accessed March 28, 2024)
Created October 11, 2006, Updated January 27, 2020