Difference between revisions of "Extracting Event-Related Information from Article Updates in Wikipedia"
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| − | '''Extracting Event-Related Information from Article Updates in Wikipedia''' - scientific work related to Wikipedia quality published in 2013, written by Mihai Georgescu, Nattiya Kanhabua, Daniel Krause, Wolfgang Nejdl and Stefan Siersdorfer. | + | '''Extracting Event-Related Information from Article Updates in Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Mihai Georgescu]], [[Nattiya Kanhabua]], [[Daniel Krause]], [[Wolfgang Nejdl]] and [[Stefan Siersdorfer]]. |
== Overview == | == Overview == | ||
| − | Wikipedia is widely considered the largest and most up-to-date online encyclopedia, with its content being continuously maintained by a supporting community. In many cases, real-life events like new scientific findings, resignations, deaths, or catastrophes serve as triggers for collaborative editing of articles about affected entities such as persons or countries. In this paper, authors conduct an in-depth analysis of event-related updates in Wikipedia by examining different indicators for events including language, meta annotations, and update bursts. Authors then study how these indicators can be employed for automatically detecting event-related updates. Authors experiments on event extraction, clustering, and summarization show promising results towards generating entity-specific news tickers and timelines. | + | Wikipedia is widely considered the largest and most up-to-date online encyclopedia, with its content being continuously maintained by a supporting community. In many cases, real-life events like new scientific findings, resignations, deaths, or catastrophes serve as triggers for collaborative editing of articles about affected entities such as persons or countries. In this paper, authors conduct an in-depth analysis of event-related updates in [[Wikipedia]] by examining different [[indicators]] for events including language, meta annotations, and update bursts. Authors then study how these indicators can be employed for automatically detecting event-related updates. Authors experiments on event extraction, clustering, and summarization show promising results towards generating entity-specific news tickers and timelines. |
Revision as of 06:49, 30 July 2019
Extracting Event-Related Information from Article Updates in Wikipedia - scientific work related to Wikipedia quality published in 2013, written by Mihai Georgescu, Nattiya Kanhabua, Daniel Krause, Wolfgang Nejdl and Stefan Siersdorfer.
Overview
Wikipedia is widely considered the largest and most up-to-date online encyclopedia, with its content being continuously maintained by a supporting community. In many cases, real-life events like new scientific findings, resignations, deaths, or catastrophes serve as triggers for collaborative editing of articles about affected entities such as persons or countries. In this paper, authors conduct an in-depth analysis of event-related updates in Wikipedia by examining different indicators for events including language, meta annotations, and update bursts. Authors then study how these indicators can be employed for automatically detecting event-related updates. Authors experiments on event extraction, clustering, and summarization show promising results towards generating entity-specific news tickers and timelines.
