David Da Costa

An interactive visualization environment for data exploration using points of interest

We present in this paper an interactive method for numeric or symbolic data visualization that allows a domain expert to extract useful knowledge and information. We propose a new approach based on points of interest (POI) but in the context of visual data mining. POIs are located on a circle, and data are displayed within this circle according to their similarities to these POI. Interactive actions are possible: selection, zoom, dynamical change of POI. We evaluate the properties of such visualization with standard data with known characteristics. We describe an industrial application which explores results from satisfaction inquiries.

On building maps of web pages with a cellular automaton

We present in this paper a clustering algorithm which is based on a cellular automaton and which aims at displaying a map of web pages. We describe the main principles of methods that build such maps, and the main principles of cellular automata. We show how these principles can be applied to the problem of web pages clustering: the cells, which are organized in a 2D grid, can be either empty or may contain a page. The local transition function of cells favors the creation of groups of similar states (web pages) in neighbouring cells. We then present the visual results obtained with our method on standard data as well as on sets of documents. These documents are thus organized into a visual map which eases the browsing of these pages.

Visualisation interactive de données avec des points d'intérêt

We present in this paper an interactive method for data visualization based on points of interest but in the context of visual data mining. Points of interest are located on a circle, and data are displayed within this circle according to their similarities to these points of interest. We evaluate the properties of such a visualization with artificial and standard data.

Generating maps of web pages using cellular automata

The aim of web pages visualization is to present in a very informative and interactive way a set of web documents to the user in order to let him or her navigate through these documents. In the web context, this may correspond to several users tasks: displaying the results of a search engine, or visualizing a graph of pages such as a hypertext or a surf map. In addition to web pages visualization, web pages clustering also greatly improves the amount of information presented to the user by highlighting the similarities between the documents [6]. In this paper we explore the use of a cellular automata (CA) to generate such maps of web pages.