Title: User Oriented Trajectory Search for Trip Recommendation
Speaker: Shuo Shang (Aalborg University)

Time: 15:00, Thursday, Aug 9th, 2012
Venue: Room 1114, 11rd Floor, Building 5#, Institute of Software, Chinese Academy of Sciences

Abstract:
Trajectory sharing and searching have received significant attentions in recent years. In this talk, I will introduce a novel problem called User Oriented Trajectory Search (UOTS) for trip recommendation. In contrast to conventional trajectory search by locations (spatial domain only), we consider both spatial and textual domains in the new UOTS query. Given a trajectory data set, the query input contains a set of intended places given by the traveler and a set of textual attributes describing the traveler’s preference. If a trajectory is connecting/close to the specified query locations, and the textual attributes of the trajectory are similar to the traveler’s preference, it will be recommended to the traveler for reference. This type of queries can bring significant benefits to travelers in many popular applications such as trip planning and recommendation. There are two challenges in the UOTS problem, (i) how to constrain the searching range in two domains and (ii) how to schedule multiple query sources effectively. To overcome the challenges and answer the UOTS query efficiently, a novel collaborative searching approach is developed. Conceptually, the UOTS query processing is conducted in the spatial and textual domains alternately. A pair of upper and lower bounds are devised to constrain the searching range in two domains. In the meantime, a heuristic searching strategy based on priority ranking is adopted for scheduling the multiple query sources, which can further reduce the searching range and enhance the query efficiency notably. Furthermore, the devised collaborative searching approach can be extended to situations where the query locations are ordered. The performance of the proposed UOTS query is verified by extensive experiments based on real and synthetic trajectory data in road networks.

Bio:
Shuo Shang is currently a faculty member of the Center for Data Intensive Systems (Daisy), Department of Computer Science, Aalborg University. He obtained his B.Sc from Peking University in 2008, and Ph.D. from the University of Queensland in 2012 respectively, both in Computer Science. During September to December 2011, he spent three months at Aarhus University as a visiting scholar hosted by Prof. Chiristian S. Jensen. During July 2011 and July 2012, he spent two months at the King Abdullah University of Science and Technology (KAUST) as a visiting research scientist hosted by Prof. Panos Kalnis. His research interests include efficient query processing in spatial-temporal databases, trajectory search and mining, uncertain data management, personalized recommendation, location based services and location based social networks.