Spatio-Temporal AI

UrbanAD:A Dual Channel Spatio-Temporal Learning Framework for Urban Anomaly Detection.

Based on artificial intelligence and big data technology, by integrating online retail data and local community consumption data, building an artificial intelligence application scenario service platform in the field of commerce and trade.

Intelligent recommendation through AI algorithm combined with multi-dimensional information collection, 360-degree restoration depicts each exhibition participant, and taps more potential business opportunities.

Based on urban multi-source big data and recommendation ranking technology, we built the first spatiotemporal intelligent recommendation engine in the field of smart cities to achieve real-time, diversified and accurate recommendations for thousands of people, thereby improving user experience and enhancing user stickiness.

Point-of-interest (POI) recommendation has become an important service to help users discover attractive locations. A variety of …

With the popularity of location-based social networks (LBSNs), Point-of-Interest (POI) recommendation has become an essential …

The increasing prevalence of location-based social networks (LBSNs) poses a wonderful opportunity to build per-sonalized …

With the thriving of location-based social networks, a large number of user check-in data have been accumulated. Tasks such as the …