Distributed Human Computation Framework for Linked Data Co-reference Resolution

Yang, Y., Singh, P., Yao, J., Au Yeung, C. M., Zareian, A., Wang, X., Cai, Z., Salvadores, M., Gibbins, N., Hall, W. and Shadbolt, N. (2011) Distributed Human Computation Framework for Linked Data Co-reference Resolution. In: 8th Extended Semantic Web Conference, LECTURE NOTES IN COMPUTER SCIENCE (LNCS), Volume 6643, 29th May - 2nd June 2011, Herakilon, Greece. pp. 32-46.

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Abstract

Distributed Human Computation (DHC) is a technique used to solve computational problems by incorporating the collaborative effort of a large number of humans. It is also a solution to AI-complete problems such as natural language processing. The Semantic Web with its root in AI is envisioned to be a decentralised world-wide information space for sharing machine-readable data with minimal integration costs. There are many research problems in the Semantic Web that are considered as AI-complete problems. An example is co-reference resolution, which involves determining whether different URIs refer to the same entity. This is considered to be a significant hurdle to overcome in the realisation of large-scale Semantic Web applications. In this paper, we propose a framework for building a DHC system on top of the Linked Data Cloud to solve various computational problems. To demonstrate the concept, we are focusing on handling the co-reference resolution in the Semantic Web when integrating distributed datasets. The traditional way to solve this problem is to design machine-learning algorithms. However, they are often computationally expensive, error-prone and do not scale. We designed a DHC system named iamResearcher, which solves the scientific publication author identity co-reference problem when integrating distributed bibliographic datasets. In our system, we aggregated 6 million bibliographic data from various publication repositories. Users can sign up to the system to audit and align their own publications, thus solving the co-reference problem in a distributed manner. The aggregated results are published to the Linked Data Cloud.

Item Type:	Conference or Workshop Item
Creator/Authors:	Yang Yang Priyanka Singh Jiadi Yao Ching Man Au Yeung Amir Zareian Xiaowei Wang Zhonglun Cai Manuel Salvadores Nicholas Gibbins Wendy Hall Nigel Shadbolt
Keywords:	Linked Data, DHC, Crowd-sourcing, Co-reference
Research Group:	Old ECS Groups > Science and Engineering of Natural Systems Current ECS Groups > Web and Internet Science Old ECS Groups > Intelligence, Agents, Multimedia Old ECS Groups > Electrical Power Engineering
Date:	29 May 2011
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ID Code:	22060
Last Modified:	23 Sep 2011 10:41
Deposited On:	23 Feb 2011 23:06 by Yang, Yang

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