Work

Learning approaches for detecting and tracking news events

Year: 1999

Type: article

Abstract: The authors extend existing supervised-learning and unsupervised-clustering algorithms to allow document classification based on the information content and temporal aspects of news events. They've adapted several IR and machine learning techniques for effective event detection and tracking. The article discusses our research using manually segmented documents.

Source: IEEE Intelligent Systems and their Applications

DOI: 10.1109/5254.784083

Authors: Y. Yang, J.G. Carbonell, R.D. Brown, T. Pierce, B.T. Archibald, X. Liu

Institution: Carnegie Mellon University

Language: English

Topic: Text and Document Classification Technologies

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2079234336

FWCI: 11.87

Cites: 28

Cited by: 339

Related to: 10