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Prioritizing Attention in Fast Data: Principles and Promise

Summary: Articulates design principles for fast-data analytics that prioritize scarce human attention—return fewer results, enable iterative workflows, and “filter fast” to compute less. Implements MacroBase, a streaming engine combining feature transforms, classification, and summarization to produce interpretable, prioritized explanations of key behaviors in high-rate data. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
283
Venue
CIDR
Year
2017
Pagerank
4.1945683e-05
Overall Rank
11,756 | 18.22%
DOI
-

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