Clustering Analysis within Text Classification Techniques

Abstract

The paper represents a personal approach upon the main applications of classification which are presented in the area of knowledge based society by means of methods and techniques widely spread in the literature. Text classification is underlined in chapter two where the main techniques used are described, along with an integrated taxonomy. The transition is made through the concept of spatial representation. Having the elementary elements of geometry and the artificial intelligence analysis, spatial representation models are presented. Using a parallel approach, spatial dimension is introduced in the process of classification. The main clustering methods are described in an aggregated taxonomy. For an example, spam and ham words are clustered and spatial represented, when the concepts of spam, ham and common and linkage word are presented and explained in the xOy space representation.

Keywords

• Knowledge Societies
• Text Classification
• Spatial Representation
• Artificial Intelligence
• Clustering Analysis
• Spam Filtering