Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach
Summary: Partial-order-based crowdsourced entity resolution; defines a pairwise order, queries a small set, and propagates to infer all answers. Grouping for cost reduction, error-tolerant handling of order and crowd errors, and efficient query selection; experiments show 1.25% of baselines (80x cheaper) with preserved quality. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chengliang Chai
- 2. Guoliang Li
- 3. Jian Li
- 4. Dong Deng
- 5. Jianhua Feng
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