Facilitating Graph Interpretation via Interactive Hierarchical Edges
نویسنده
چکیده
Graphs visualizations can become difficult to interpret when they fail to highlight patterns. Additionally, the data to be visualized may be hierarchical in nature. Therefore, graphs with hierarchical data need to offer means of telescoping that collapse or expand subgraphs while aggregating their data. In this paper, we demonstrate an interactive hierarchical edge graph on book prerequisite data, which can be generalized to a variety of hierarchical data. We illustrate the importance of ordering nodes (when possible) and coloring by various features. We then demonstrate various ways of performing exploratory data analysis by delivering various pieces of information on mouseovers and utilizing telescoping and filtering.
منابع مشابه
A Model Browser for Biosimulation
The complexities of biological simulation present difficulties with modeling and experimenting. Simulators process models represented as code, whereas biologists think about abstract models. Our ModelBrowser addresses this difficulty through interactive visualization. Variables and equations appear as a directed graph of nodes and edges, and the user can search and browse this graph by performi...
متن کاملخوشهبندی اسناد مبتنی بر آنتولوژی و رویکرد فازی
Data mining, also known as knowledge discovery in database, is the process to discover unknown knowledge from a large amount of data. Text mining is to apply data mining techniques to extract knowledge from unstructured text. Text clustering is one of important techniques of text mining, which is the unsupervised classification of similar documents into different groups. The most important step...
متن کاملCarina: Interactive Million-Node Graph Visualization using Web Browser Technologies
We are working on a scalable, interactive visualization system, called Carina, that helps people explore million-node graphs. By using latest web browser technologies, Carina offers fast graph rendering via WebGL and works across desktop (via Electron) and mobile platforms. Different from most existing graph visualization tools, Carina does not store the full graph in RAM, enabling it to work w...
متن کاملTaxonomy Induction Using Hierarchical Random Graphs
This paper presents a novel approach for inducing lexical taxonomies automatically from text. We recast the learning problem as that of inferring a hierarchy from a graph whose nodes represent taxonomic terms and edges their degree of relatedness. Our model takes this graph representation as input and fits a taxonomy to it via combination of a maximum likelihood approach with a Monte Carlo Samp...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014