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Wen-Fang Lu

dblp:351/9906 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0005-5866-1770ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 56% Web and social media mining · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Web and social media mining
event detection
0.712023
MetroScope: An Advanced System for Real-Time Detection and Analysis of Metro-Related Threats and Events via Twitter · SIGIR 2023
Information retrieval › document retrieval › temporal information retrieval
new event detection
0.712023
MetroScope: An Advanced System for Real-Time Detection and Analysis of Metro-Related Threats and Events via Twitter · SIGIR 2023
Information retrieval
content-based retrieval
0.212023
MetroScope: An Advanced System for Real-Time Detection and Analysis of Metro-Related Threats and Events via Twitter · SIGIR 2023
YearPublicationVenuePosition
2023 MetroScope: An Advanced System for Real-Time Detection and Analysis of Metro-Related Threats and Events via Twitter
abstract
Metro systems are vital to our daily lives, but they face safety or reliability challenges, such as criminal activities or infrastructure disruptions, respectively. Real-time threat detection and analysis are crucial to ensure their safety and reliability. Although many existing systems use Twitter to detect metro-related threats or events in real-time, they have limitations in event analysis and system maintenance. Specifically, they cannot analyze event development, or prioritize events from numerous tweets. Besides, their users are required to continuously monitor system notifications, use inefficient content retrieval methods, and perform detailed system maintenance. We addressed those issues by developing the MetroScope system, a real-time threat/event detection system applied to Washington D.C. metro system. MetroScope can automatically analyze event development, prioritize events based on urgency, send emergency notifications via emails, provide efficient content retrieval, and self-maintain the system. Our MetroScope system is now available at http://orion.nvc.cs.vt.edu:5000/, with a video (https://www.youtube.com/watch?v=vKIK9M60-J8) introducing its features and instructions. MetroScope is a significant advancement in enhancing the safety and reliability of metro systems.
Syuan-Ying Wu, Abdulaziz Alhamadani, Chih-Fang Chen, Wen-Fang Lu, Chang-Tien Lu, David Solnick, Yanlin Li 0008
SIGIR5