Spatial databases

Next Generation Location-Based Social Networks

Researchers: Associate Professor Muhammad Cheema
Professor Wei Wang (UNSW)
Professor Mohamed Mokbel (University of Minnesota)

This project aims to design effective and intelligent search techniques for large-scale social network data. We’ll focus on three unique aspects: using the geographical locations of queries and social network data to provide more relevant results, acknowledging and handling inherent uncertainties in the data and exploiting knowledge graphs to produce intelligent search results. The outcomes of this initiative will support and enhance a wide range of applications in law enforcement, health, national security, marketing and advertising.

Indoor Data Management

Researchers: Associate Professor Muhammad Cheema

Efficient data management techniques are key to providing indoor location-based services on a global scale. This project aims to design and test techniques that are efficient, adapted to the ontology of indoor spaces and capable of handling uncertainties in data, rich textual information associated with location data and historical location data.

In Search of Points of Interest in Road Networks

Researchers: Associate Professor Muhammad Cheema

Modern map-based systems and location-based services rely heavily on the ability to efficiently search points of interests (POIs) based on their location or textual information. The aim of this project is to build a next-generation POI search system by addressing limitations in the current systems – such as allowing more meaningful distance measures, modeling uncertainty in data sources and queries, and exploiting rich information from several data sources.