UNDERSTANDING GRAPHS AND TABLES

Understanding Tables on the Web

The Web contains a wealth of information, and a key challenge is to make this information machine processable. Because natural language understanding at web scale remains difficult and costly at present, in this paper, we focus our attention on understanding well-structured html tables on the Web. From 0.3 billion Web documents, we obtain 1.95 billion tables, and 0.5-1% of these contain meaning...

Informative Presentation of Tables, Graphs and Statistics

Task-dependent processing of tables and graphs

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Understanding Uncertainty in School League Tables*

In England, contextual value added (CVA) school performance tables are published annually by the government. These tables present statisticalmodel-based estimates of the educational effectiveness of schools, together with 95 per cent confidence intervals to communicate their statistical uncertainty. However, this information, particularly the notion of statistical uncertainty, is hard for users...

Summarizing and understanding large graphs

How can we succinctly describe a million-node graph with a few simple sentences? Given a large graph, how can we find its most ‘important’ structures, so that we can summarize it and easily visualize it? How can we measure the ‘importance’ of a set of discovered subgraphs in a large graph? Starting with the observation that real graphs often consist of stars, bipartite cores, cliques and chains...