Refining Automatically Extracted Knowledge Bases Using Crowdsourcing
Joint Authors
Cui, Zhiming
Li, Chunhua
Zhao, Pengpeng
Wu, Jian
Xian, Xuefeng
Sheng, Victor S.
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-14
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Machine-constructed knowledge bases often contain noisy and inaccurate facts.
There exists significant work in developing automated algorithms for knowledge base refinement.
Automated approaches improve the quality of knowledge bases but are far from perfect.
In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases.
As human labelling is costly, an important research challenge is how we can use limited human resources to maximize the quality improvement for a knowledge base.
To address this problem, we first introduce a concept of semantic constraints that can be used to detect potential errors and do inference among candidate facts.
Then, based on semantic constraints, we propose rank-based and graph-based algorithms for crowdsourced knowledge refining, which judiciously select the most beneficial candidate facts to conduct crowdsourcing and prune unnecessary questions.
Our experiments show that our method improves the quality of knowledge bases significantly and outperforms state-of-the-art automatic methods under a reasonable crowdsourcing cost.
American Psychological Association (APA)
Li, Chunhua& Zhao, Pengpeng& Sheng, Victor S.& Xian, Xuefeng& Wu, Jian& Cui, Zhiming. 2017. Refining Automatically Extracted Knowledge Bases Using Crowdsourcing. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-17.
https://search.emarefa.net/detail/BIM-1140926
Modern Language Association (MLA)
Zhao, Pengpeng…[et al.]. Refining Automatically Extracted Knowledge Bases Using Crowdsourcing. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-17.
https://search.emarefa.net/detail/BIM-1140926
American Medical Association (AMA)
Li, Chunhua& Zhao, Pengpeng& Sheng, Victor S.& Xian, Xuefeng& Wu, Jian& Cui, Zhiming. Refining Automatically Extracted Knowledge Bases Using Crowdsourcing. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-17.
https://search.emarefa.net/detail/BIM-1140926
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1140926