We describe a package of practical tools and libraries for manipulating graphs and their drawings. Our design, which is aimed at facilitating the combination of the package components with other tools, includes stream and event interfaces for graph operations, high‐quality static and dynamic layout algorithms, and the ability to handle sizeable graphs. We conclude with a description of the applications of this package to a variety of software engineering tools. Copyright © 2000 John Wiley & Sons, Ltd.

No abstract

Recently, we have developed a software able of gathering information on social networks from written texts. This software, the CHAracters and PLaces Interaction Network (CHAPLIN) tool, is implemented in Visual Basic. By means of it, characters and places of a literary work can be extracted from a list of raw words. The software interface helps users to select their names out of this list. Setting some parameters, CHAPLIN creates a network where nodes represent characters/places and edges give their interactions. Nodes and edges are labelled by performances. In this paper, we propose to use CHAPLIN for the analysis a William Shakespeare's play, the famous "Tragedy of Hamlet, Prince of Denmark". Performances of characters in the play as a whole and in each act of it are given by graphs.Here, we are proposing an example of using CHAPLIN, by applying it to the analysis a William Shakespeare's play, the famous "Tragedy of Hamlet, Prince of Denmark". After a short discussion of CHAPLIN, the graphs for the overall play and for each act of it will be displayed.This article is published at:

Abstract. One of the most popular graph drawing methods is based on achieving graph-theoretic target distances. This method was used by Kamada and Kawai [15], who formulated it as an energy optimization problem. Their energy is known in the multidimensional scaling (MDS) community as the stress function. In this work, we show how to draw graphs by stress majorization, adapting a technique known in the MDS community for more than two decades. It appears that majorization has advantages over the technique of Kamada and Kawai in running time and stability. We also found the majorization-based optimization being essential to a few extensions to the basic energy model. These extensions can improve layout quality and computation speed in practice.

No abstract

No abstract

No abstract

Abstract-Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful in exploratory data analysis, they need to be adapted to human needs and domain-specific problems, ideally, interactively, and on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating DR with interactive visualizations. Nevertheless, a general, structured understanding of this integration is missing. To address this, we systematically studied the visual analytics and visualization literature to investigate how analysts interact with automatic DR techniques. The results reveal seven common interaction scenarios that are amenable to interactive control such as specifying algorithmic constraints, selecting relevant features, or choosing among several DR algorithms. We investigate specific implementations of visual analysis systems integrating DR, and analyze ways that other machine learning methods have been combined with DR. Summarizing the results in a "human in the loop" process model provides a general lens for the evaluation of visual interactive DR systems. We apply the proposed model to study and classify several systems previously described in the literature, and to derive future research opportunities.