Human computing games for knowledge acquisition

Kumar Kondredi, S., Triantafillou, P. and Weikum, G. (2013) Human computing games for knowledge acquisition. In: ACM Conference On Information and Knowledge Management, (CIKM13), San Francisco, CA, USA, 27 Oct - 1 Nov 2013, (doi: 10.1145/2505515.2508213)

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Automatic information extraction techniques for knowledge acquisition are known to produce noise, incomplete or incorrect facts from textual sources. Human computing offers a natural alternative to expand and complement the output of automated information extraction methods, thereby enabling us to build high-quality knowledge bases. However, relying solely on human inputs for extraction can be prohibitively expensive in practice. We demonstrate human computing games for knowledge acquisition that employ human computing to overcome the limitations in automated fact acquisition methods. We provide a combined approach that tightly integrates automated extraction techniques with human computing for effective gathering of facts. The methods we provide gather facts in the form of relationships between entities. The games we demonstrate are specifically designed to capture hard-to-extract relations between entities in narrative text -- a task that automated systems find challenging.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Triantafillou, Professor Peter
Authors: Kumar Kondredi, S., Triantafillou, P., and Weikum, G.
College/School:College of Science and Engineering > School of Computing Science

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