BibSonomyburst/user/lee_peck/visualizationBibSonomy RSS feed for /user/lee_peck/visualization2012-02-16T22:54:22+01:00http://www.bibsonomy.org/bibtex/2c27813d7de06e606f6d3367e32711766/lee_pecklee_peck2008-11-12T20:59:49+01:00Toyoda05evolutionVisualization graph toread visualization <span class="authorEditorList"><a href="/author/Toyoda">Masashi Toyoda</a>, and <a href="/author/Kitsuregawa">Masaru Kitsuregawa</a> </span><em>HYPERTEXT &#039;05: Proceedings of the sixteenth ACM conference on Hypertext and hypermedia, </em><em>page 151--160. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2005</em>)Wed Nov 12 20:59:49 CET 2008New York, NY, USAHYPERTEXT '05: Proceedings of the sixteenth ACM conference on Hypertext and hypermedia151--160A system for visualizing and analyzing the evolution of the web with a time series of graphs2005Toyoda05evolutionVisualization graph toread visualization We propose WebRelievo, a system for visualizing and analyzing the evolution of the web structure based on a large Web archive with a series of snapshots. It visualizes the evolution with a time series of graphs, in which nodes are web pages, and edges are relationships between pages. Graphs can be clustered to show the overview of changes in graphs. WebRelievo aligns these graphs according to their time, and automatically determines their layout keeping positions of nodes synchronized over time, so that the user can keep track pages and clusters. This visualization enables us to understand when pages appeared, how their relationships have evolved, and how clusters are merged and split over time. Current implementation of WebRelievo is based on six Japanese web archives crawled from 1999 to 2003. The user can interactively browse those graphs by changing the focused page and by changing layouts of graphs. Using WebRelievo we can answer historical questions, and to investigate changes in trends on the Web. We show the feasibility of WebRelievo by applying it to tracking trends in P2P systems and search engines for mobile phones, and to investigating link spamming.A system for visualizing and analyzing the evolution of the web with a time series of graphs