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Conference Paper
Query Transformation for Approximate Query Processing Using Synthetic Data from Deep Generative Models
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- Authors
- Taewhi Lee, Choon Seo Park, Kihyuk Nam, Sung-Soo Kim
- Issue Date
- 2022-10
- Citation
- International Conference on Consumer Electronics (ICCE) 2022 : Asia, pp.314-317
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- In exploratory data analysis, interactive latency can make a significant impact on the data exploration space and user productivity. To provide low latency for the aggregation query, approximate query processing can be considered as a possible alternative. In this paper, we describe the transformation rules for processing approximation queries. We present the preliminary experimental results on the performance of approximate query processing with synthetic data.
- KSP Keywords
- Aggregation query, Approximate query processing, Generative models, Interactive Latency, Low latency, Query transformation, Synthetic data, Transformation rules, data exploration, exploratory data analysis