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Declarative Data Analytics: A Survey

delete2021-06-01
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OA
AI
N
Nantia Makrynioti *
V
Vasilis Vassalos
DOI：10.1109/TKDE.2019.2958084delete
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Abstract

Abstract

En 中文
The area of declarative data analytics explores the application of the declarative paradigm on data science and machine learning. It proposes declarative languages for expressing data analysis tasks and develops systems which optimize programs written in those languages. The execution engine can be either centralized or distributed, as the declarative paradigm advocates independence from particular physical implementations. The survey explores a wide range of declarative data analysis frameworks by examining both the programming model and the optimization techniques used, in order to provide conclusions on the current state of the art in the area and identify open challenges.
Keywords:
Task analysis
Data analysis
Programming
Optimization
Mathematical model
Analytical models
Prediction algorithms
Declarative programming
data science
machine learning
large-scale analytics
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Knowledge and Data Engineering cover
IEEE Transactions on Knowledge and Data Engineering
IF:
10.4
Papers:
6.8K
Citations:
3.2W

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