Combining information extraction and human computing for crowdsourced knowledge acquisition
- Submitting institution
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The University of Warwick
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6120
- Type
- E - Conference contribution
- DOI
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10.1109/ICDE.2014.6816717
- Title of conference / published proceedings
- 2014 IEEE 30th International Conference on Data Engineering
- First page
- 988
- Volume
- -
- Issue
- -
- ISSN
- 1063-6382
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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D - Data Science, Systems and Security
- Citation count
- 24
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published at a top conference in the field, this paper was the first to propose improving Knowledge Acquisition (KA) with human intelligence. The proposed KA process integrated a semantic-enrichment tool and a novel human-computing gaming environment, which by leveraging human intelligence drastically reduced automated information extraction errors while enriching the Knowledge Base with new facts. A real-world artefact was developed and incorporated within the YAGO Knowledge Base, and demonstrated at the prestigious CIKM and WWW conferences. The paper is well cited in the most reputable venues in data management, data analytics, and data mining.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -