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Beyond Artificial Reality: Finding and Monitoring Live Events from Social Sensors

ACM Transactions on Internet Technology, ISSN: 1557-6051, Vol: 20, Issue: 1, Page: 1-21
2020
  • 5
    Citations
  • 0
    Usage
  • 33
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

Article Description

With billions of active social media accounts and millions of live video cameras, live new big data offer many opportunities for smart applications. However, the main consumers of the new big data have been humans. We envision the research on live knowledge, to automatically acquire real-time, validated, and actionable information. Live knowledge presents two significant and diverging technical challenges: big noise and concept drift. We describe the EBKA (evidence-based knowledge acquisition) approach, illustrated by the LITMUS landslide information system. LITMUS achieves both high accuracy and wide coverage, demonstrating the feasibility and promise of EBKA approach to achieve live knowledge.

Bibliographic Details

Calton Pu; Abhijit Suprem; Rodrigo Alves Lima; Aibek Musaev; De Wang; Danesh Irani; Steve Webb; Joao Eduardo Ferreira

Association for Computing Machinery (ACM)

Computer Science

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