Automated Big Data Quality Assessment using Knowledge Graph Embeddings
A new approach to automated data quality assessment using knowledge graph embeddings has been proposed. This method aims to enhance the accuracy of context-aware assessments by predicting missing edges in datasets. The evaluation of this approach, using a real-world dataset, demonstrates its effectiveness in generating comprehensive data quality assessment plans.
- ▪Automated data quality assessment is essential for managing big data effectively.
- ▪The proposed method integrates knowledge graph embeddings to improve context-aware assessments.
- ▪Evaluation results indicate that the approach can create detailed data quality assessment plans.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Machine Learning arXiv:2605.18833 (cs) [Submitted on 12 May 2026] Title:Automated Big Data Quality Assessment using Knowledge Graph Embeddings Authors:Hadi Fadlallah, Rima Kilany, Mitri Haber, Ali Jaber View a PDF of the paper titled Automated Big Data Quality Assessment using Knowledge Graph Embeddings, by Hadi Fadlallah and 3 other authors View PDF HTML (experimental) Abstract:Automated data quality assessment is crucial for managing big data, but existing solutions face challenges in achieving accurate context-aware assessment. This paper presents a novel knowledge-based approach to enhance automated data quality assessment.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
Discussion
0 commentsMore from arXiv cs.AI
