---
title: "Using a Bayesian Network Induction Approach for Text Categorization"
authors:
  - "Wai Lam"
  - "Kon Fan Low"
  - "Chao Yang Ho"
doi: ""
url: "https://ijcai.org/proceedings/1997/108"
pdf: "https://ijcai.org/proceedings/1997/0108.pdf"
venue: "Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence"
year: 1997
pages: "745-749"
track: "Information Retrieval"
keywords:
---

# Using a Bayesian Network Induction Approach for Text Categorization

Wai Lam, Kon Fan Low, Chao Yang Ho

*Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence*, pages 745-749.

## Abstract

We investigate Bayesian methods for automatic document categorization and develop a new approach to this problem. Our new approach is based on a Bayesian network induction which does not rely on some major assumptions found in a previous method using the Bayesian independence classifier approach. The design of the new approach as well as its justification are presented. Experiments were conducted using a large-scale document co ll ection from Reuters news articles. The results show that our approach outperformed the Bayesian independence classifier as measured by a metric that combines precision and recall measures.