GA-Based Keyword Selection for the Design of an Intelligent Web Document Search System
The main steps for designing an automatic document classification system include feature extraction and classification. In this article a method to improve feature extraction is proposed. In this method, genetic algorithm was applied to determine the threshold values of four criteria for extracting the representative keywords for each class. The purpose of these four threshold values is to extract as few representative keywords as possible. This keyword extraction method was combined with two classification algorithms, vector space model and support vector machine, for examining the performance of the proposed classification system under various extracting conditions.
genetic algorithm keyword extraction support vector machine web document classification vector space method