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Conference Paper

HIGGINS: Knowledge Acquisition Meets the Crowds

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Kondreddi,  Sarath Kumar
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Citation

Kondreddi, S. K., Triantafillou, P., & Weikum, G. (2013). HIGGINS: Knowledge Acquisition Meets the Crowds. In D. Schwabe, V. Almeida, H. Glaser, R. Baeza-Yates, & S. Moon (Eds.), WWW'13 (pp. 85-86). New York, NY: ACM. Retrieved from http://dl.acm.org/citation.cfm?id=2487788.2487825.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0015-1B79-4
Abstract
We present HIGGINS, a system for \em Knowledge Acquisition (KA)}, placing emphasis on its architecture. The distinguishing characteristic and novelty of HIGGINS lies in its blending of two engines: an automated {\em Information Extraction (IE)} engine, aided by {\em semantic resources} and {\em statistics}, and a game-based {\em Human Computing (HC) engine. We focus on KA from web pages and text sources and, in particular, on deriving relationships between entities. As a running application we utilize movie narratives, from which we wish to derive relationships among movie characters.