A new association rule-based text classifier algorithm

Buddeewong, Supaporn; Kreesuradej, Worapoj

doi:10.1109/ICTAI.2005.13

A new association rule-based text classifier algorithm

Author(s)

Buddeewong, Supaporn

Kreesuradej, Worapoj

Date Issued

January 1, 2005

Type

Conference Paper

DOI

10.1109/ICTAI.2005.13

Abstract

This paper proposes a new association rule-based text classifier algorithm to improve the prediction accuracy of Association Rule-based Classifier By Categories (ARC-BC) algorithm. Unlike the previous algorithms, the proposed association rule generation algorithm constructs two types of frequent itemsets. The first frequent itemsets, i.e. Lk, contain all term that have no an overlap with other categories. The second frequent itemsets, i.e. OL k, contain all features that have an overlap with other categories. In addition, this paper also proposes a new join operation for the second frequent itemsets. The experimental results are shown a good performance of the proposed classifier © 2005 IEEE.

Citation

Proceedings International Conference on Tools with Artificial Intelligence Ictai, 2005, 684-685, 2005