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      Hedera: Scalable Indexing and Exploring Entities in Wikipedia Revision History

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          Abstract

          Much of work in semantic web relying on Wikipedia as the main source of knowledge often work on static snapshots of the dataset. The full history of Wikipedia revisions, while contains much more useful information, is still difficult to access due to its exceptional volume. To enable further research on this collection, we developed a tool, named Hedera, that efficiently extracts semantic information from Wikipedia revision history datasets. Hedera exploits Map-Reduce paradigm to achieve rapid extraction, it is able to handle one entire Wikipedia articles revision history within a day in a medium-scale cluster, and supports flexible data structures for various kinds of semantic web study.

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          Author and article information

          Journal
          2017-01-14
          Article
          1701.03937
          4bcd5c41-d8bd-4068-b4f9-1153ce6da5e9

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          Pubished via CEUR-WS.org/Vol-1272
          cs.AI cs.IR

          Information & Library science,Artificial intelligence
          Information & Library science, Artificial intelligence

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