{"paper":{"title":"r-HUMO: A Risk-Aware Human-Machine Cooperation Framework for Entity Resolution with Quality Guarantees","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.HC","authors_text":"Boyi Hou, Qun Chen, Youcef Nafa, Zhanhuai Li, Zhaoqiang Chen","submitted_at":"2018-03-15T12:45:46Z","abstract_excerpt":"Even though many approaches have been proposed for entity resolution (ER), it remains very challenging to find one with quality guarantees. To this end, we proposea risk-aware HUman-Machine cOoperation framework for ER, denoted by r-HUMO. Built on the existing HUMO framework, r-HUMO similarly enforces both precision and recall levels by partitioning an ER workload between the human and the machine. However, r-HUMO is the first solution to optimize the process of human workload selection from a risk perspective. It iteratively selects human workload based on real-time risk analysis on human-lab"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.05714","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}