Amplifying community content creation with mixed initiative information extraction

Although existing work has explored both information extraction and community content creation, most research has focused on them in isolation. In contrast, we see the greatest leverage in the synergistic pairing of these methods as two interlocking feedback cycles. This paper explores the potential synergy promised if these cycles can be made to accelerate each other by exploiting the same edits to advance both community content creation and learning-based information extraction. We examine our proposed synergy in the context of Wikipedia infoboxes and the Kylin information extraction system. After developing and refining a set of interfaces to present the verification of Kylin extractions as a non-primary task in the context of Wikipedia articles, we develop an innovative use of Web search advertising services to study people engaged in some other primary task. We demonstrate our proposed synergy by analyzing our deployment from two complementary perspectives: (1) we show we acceler...

• Type: Conference
• Year: 2009
• Where: CHI
• Authors: Raphael Hoffmann, Saleema Amershi, Kayur Patel, Fei Wu, James Fogarty, Daniel S. Weld
• Keywords: CHI 2009, Community Content Creation, Human Computer Interaction, Information Extraction, Information Extraction System