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CrowdER: Crowdsourcing Entity Resolution Joanna Wang # Tim Alaska Michael J. Franklin Diana Fend # # AMP Lab, UC Berkeley Department of Computer Science, Tsinghua University wjn08 mails.Songhua.edu.CN;
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Crowder crowdsourcing entity resolution is a process where a group of people collectively work to identify and match different entities or records in a dataset to establish their connections or relationships.
The organization or entity that owns the dataset and wishes to resolve the entities within it is required to file crowder crowdsourcing entity resolution.
To fill out crowder crowdsourcing entity resolution, participants are usually provided with a platform or tool that allows them to view the dataset, compare different entities, and provide their judgments or decisions about their similarities or matches.
The purpose of crowder crowdsourcing entity resolution is to leverage the collective intelligence and diverse perspectives of a group of individuals to accurately and efficiently resolve complex entity matching tasks that might be challenging for automated algorithms.
The specific information that must be reported on crowder crowdsourcing entity resolution can vary depending on the nature of the dataset and the entity resolution task. Generally, participants may need to provide their judgments or decisions on the match or non-match status of different attributes or fields of the entities being resolved.
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