Visualization of the Document Data in a Information Retrieval Clustering Model

Abstract

Recently, the document data of news, websites and papers have accumulated in the database every year. And the amount of information increases substantially. Therefore, we can not understand and search the matter from all data. In this paper, we proposed a new clustering model for information retrieval using kernel aggolomerative hierarchical clustering(KAHC). Moreover, we show a new visualization technique for the result of data using KAHC and kernel Fisher discriminant analysis(Kernel-FDA). This visually will be able to verify information on related to the result of the information data. As a result, the data that was classified on the feature space can be visualized on the low dimentional space. Through some examples, we show to display the retrieval result more effectively becomes possible.