knowledge graphs ↔ data cleaning

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related 0.30 — supporting 3 facts

Data cleaning is a critical component of the construction and maintenance process for knowledge graphs, as evidenced by [1], [2], and [3], which highlight its role in ensuring data quality, error removal, and overall system improvement.

Facts (3)

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Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org arXiv 2 facts

claimData cleaning in knowledge graphs involves detecting and removing errors and inconsistencies to improve data quality.

claimQuality improvement for knowledge graphs includes data cleaning, error correction, outlier detection, entity resolution, data fusion, and continuous ontology development.

Practices, opportunities and challenges in the fusion of knowledge ... frontiersin.org Frontiers 1 fact

claimConstructing and maintaining high-quality knowledge graphs typically involves significant human effort, including data cleaning, entity alignment, relation labeling, and expert validation, which is particularly labor-intensive in domains requiring expert knowledge.