Accurate Entity Resolution using Crowdsourcing

王 晶晶; 小山 聡; 栗原 正仁; 鹿島 久嗣

doi:10.11517/pjsai.JSAI2013.0_2M5OS07b3

Proceedings of the Annual Conference of JSAI

Online ISSN : 2758-7347

27th (2013)

Session ID : 2M5-OS-07b-3

DOI https://doi.org/10.11517/pjsai.JSAI2013.0_2M5OS07b3

Conference information

Host: The Japanese Society for Artificial Intelligence

Name : The 27th Annual Conference of the Japanese Society for Artificial Intelligence, 2013

Number : 27

Location : [in Japanese]

Date : June 04, 2013 - June 07, 2013

Accurate Entity Resolution using Crowdsourcing

*[in Japanese], [in Japanese], [in Japanese], [in Japanese]

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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

We propose a supervised learning method to derive an accurate model for entity resolution using crowd-generated data. Begin with discussion on the accuracy of crowd-generated labels, we evaluate the accuracy of our proposed method.

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