Exploiting Domain Knowledge to address Multi-Class Imbalance and a Heterogeneous Feature Space in Classification Tasks for Manufacturing Data
Summary: Exploits domain knowledge to jointly tackle multi-class imbalance and heterogeneous feature space in manufacturing end-of-line classification. Domain-guided data prep yields a classifier that outperforms baselines and reduces rework on real-world quality data. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Vitali Hirsch
- 2. Peter Reimann
- 3. Bernhard Mitschang
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,716 | Chimera: Large-Scale Classification using Machine Learning, Rules, and Crowdsourcing | 2014 | VLDB | 0.00010795718 |
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