Discovering the Power of Civilcomputing

Civil Computing leverages interactive visualized data exploration frameworks to bring big data back to a human scale, to make big data empower everyone for optimal decision making and facilitate people’s everyday life. Civil computing problems involves three domains: (1) House Seeking (Point of Interest and Area of Interest) (2) Facility Deployment, and (3) Intelligent Transport.

• House Seeking
• Map-based Visual exploration on location-centred multi-dimensional data (WSDM’19, EuroVIS’18, JVLC’18)
• Map-based Spatial Object Recommendation with Explainability (SIGIR’20)
• Representative Spatial Object Selection (SIGMOD’18)
• Realtime Popular House (POI) and Area (AOI) Monitoring (ICDE’17)
• Facility Deployment
• Towards an Optimal City-wide Deployment of Advertisement (for Influcence Maximization) and Deployment of Gas stations, electric charging stations and any Facilities (for Doverage Maximization).
• Orthogonal to different choices of Coverage Measurement and Influence Measurement.
• When the Influence Overlaps Matter (KDD’18, TKDD’20)
• When the Impression Counts Matter (KDD’19)
• Optimal Site Selection for Retailer Store (VLDB’18)
• Intelligent Transport
• From the perspective of transport service provider, we exploit user movement data to:
• Monitor Network-wide Traffic via Vehicle Trajectory Clustering (PVLDB’20)
• Bring People back to Public Transport via Reoptimizing the Bus Route Network (TKDE’19)
• Ehance Passengers’ Satisfaction via Optimizing the Network-wide Public Transport Time Schedule (DASFAA’20 and more on the way)
• Dynamic Ridesharing in Peak Travel Periods to Boost User Satisfaction (TKDE’20)
• From the perspective of individual user, we exploit user movement data to:
• Estimate the Origin-Destination Travel Time for a trip (SIGMOD’20)
• Build an All-purpose POI and Trajectory Search Engine for Personalized Trip Planning (ICDE’17, SIGIR’18, WSDM’18)
• Clean and Integrate Massive Trajectory Data (SIGMOD’18)