VisualWikiCurator: human and machine intelligencefor organizing wiki content

Authors:
Nicholas Kong;Ben Hanrahan;Thiébaud Weksteen;Gregorio Convertino;Ed H. Chi
Affiliations:
Palo Alto Research Center, Palo Alto, CA, USA;Palo Alto Research Center, Palo Alto, CA, USA;Xerox Research Centre Europe, Meylan, France;Palo Alto Research Center, Palo Alto, CA, USA;Palo Alto Research Center, Palo Alto, CA, USA
Venue:
Proceedings of the 16th international conference on Intelligent user interfaces
Year:
2011

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Abstract

Corporate wikis are affected by poor adoption rates. The high interaction costs required to organize and maintain information in these wikis are a key factor that limits broader adoption. We present VisualWikiCurator, a wiki extension designed to lower such costs by (a) recommending new content to easily update a wiki page, and (b) extracting structured data from the wiki page while providing new alternative visualizations of the data. The visualizations of extracted semantic data act both as alternative views and as tools to organize the page content. Since no information extraction algorithm is perfect with generic unstructured data, we use a mixed-initiative approach to allow users to refine machine-extracted metadata and easily re-organize the content in wiki pages.