2009
DOI: 10.1007/978-3-642-02121-3_79
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Demo: HistoryViz – Visualizing Events and Relations Extracted from Wikipedia

Abstract: HistoryViz provides a new perspective on a certain kind of textual data, in particular the data available in the Wikipedia, where different entities are described and put in historical perspective. Instead of browsing through pages each describing a certain topic, we can look at the relations between entities and events connected with the selected entities. The presented solution implemented in HistoryViz provides user with a graphical interface allowing viewing events concerning the selected person on a timel… Show more

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Cited by 4 publications
(4 citation statements)
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“…The Web application HistoryViz displays events related to a queried person on a timeline. Apart from this visualization, the system also features a Java applet graph visualization of Wikipedia pages (Sipos et al 2009). The system relies on algorithms for categorization of Wikipedia articles into persons, places or organizations (Bhole et al 2007).…”
Section: Graphical Extensionsmentioning
confidence: 99%
“…The Web application HistoryViz displays events related to a queried person on a timeline. Apart from this visualization, the system also features a Java applet graph visualization of Wikipedia pages (Sipos et al 2009). The system relies on algorithms for categorization of Wikipedia articles into persons, places or organizations (Bhole et al 2007).…”
Section: Graphical Extensionsmentioning
confidence: 99%
“…There are some works that use Wikipedia to extract events and summarize them, such as [37,38], but they do not make use of the edit history. By using facts extracted from just one version of Wikipedia, a visualization tool for events and relationships in Wikipedia is proposed in [39]. The authors of [40] investigate the summarization of edits occurring in a time period as a tag cloud, finding a correlation between the popularity of a topic and the number of updates, and they make a visualization available.…”
Section: Event Summarization In Wikipediamentioning
confidence: 99%
“…Finally, a great amount of work has gone into visualising information that is readily available in the form of time-labelled events [10,6].…”
Section: Related Workmentioning
confidence: 99%