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<p>Stream processing and real-time applications have changed how data is collected and processed. However, data quality is crucial for its usefulness. In this paper, we introduce Ada-Context, an approach that uses external contextual information to improve data quality assessment. It involves offline and online analysis components and uses a grid structure to map streaming data to cells, enhancing performance of quality control in data streams. Results show that contextual data especially external context improves data cleansing accuracy and the grid design boosts quality control effectiveness for data streams.</p>

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Ada-Context: adaptive context-aware grid-based approach for curation of data streams

  • 期刊论文

  • 发表日期：

    2025年3月20日

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  • Mostafa Mirzaie,
  • Behshid Behkamal,
  • Mohammad Allahbakhsh,
  • Samad Paydar,
  • Elisa Bertino

摘要

Stream processing and real-time applications have changed how data is collected and processed. However, data quality is crucial for its usefulness. In this paper, we introduce Ada-Context, an approach that uses external contextual information to improve data quality assessment. It involves offline and online analysis components and uses a grid structure to map streaming data to cells, enhancing performance of quality control in data streams. Results show that contextual data especially external context improves data cleansing accuracy and the grid design boosts quality control effectiveness for data streams.