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CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning
Summary: CtxPipe automates context-aware data-prep pipeline construction for ML using pretrained embeddings to capture semantics and guide component choice. A deep RL framework searches the pipeline, delivering higher feature quality and faster models.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
h0ad1e9cd7e0e1803
Venue
SIGMOD
Year
2024
Pagerank
5.7678369e-05
Overall Rank
6,438 | 56.85%
DOI
10.1145/3698831
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(CC BY 4.0)
Incoming Non-self Citations Over Time
BibTeX Citation
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@inproceedings{gao_sigmod24,
title = {{CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning}},
author = {Gao, Haotian and Cai, Shaofeng and Dinh, Tien Tuan Anh and Huang, Zhiyong and Ooi, Beng Chin},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3698831},
url = {https://dl.acm.org/doi/10.1145/3698831},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
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948
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2019
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2,116
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities
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2,451
Approximate Denial Constraints
2020
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2,685
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3,420
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2017
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3,970
DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data
2023
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4,245
Scalable Discovery of Unique Column Combinations
2014
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2020
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5,230
Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications
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