O
Ouri Wolfson
Researcher at University of Illinois at Chicago
Publications - 238
Citations - 12123
Ouri Wolfson is an academic researcher from University of Illinois at Chicago. The author has contributed to research in topics: Mobile computing & Dissemination. The author has an hindex of 50, co-authored 237 publications receiving 11442 citations. Previous affiliations of Ouri Wolfson include University of Chicago & Florida International University.
Papers
More filters
Journal ArticleDOI
Urban Computing: Concepts, Methodologies, and Applications
TL;DR: The concept of urban computing is introduced, discussing its general framework and key challenges from the perspective of computer sciences, and the typical technologies that are needed in urban computing are summarized into four folds.
Proceedings ArticleDOI
Modeling and querying moving objects
TL;DR: This work proposes a data model for representing moving objects in database systems called the Moving Objects Spatio-Temporal (MOST) data model, and devise an algorithm for processing FTL queries in MOST.
Proceedings ArticleDOI
Moving objects databases: issues and solutions
TL;DR: The objective of the Databases fOr MovINg Objects (DOMINO) project is to build an envelope containing a critical set of capabilities that are needed by moving object database applications and are lacking in existing DBMSs.
Proceedings ArticleDOI
T-share: A large-scale dynamic taxi ridesharing service
Shuo Ma,Yu Zheng,Ouri Wolfson +2 more
TL;DR: The dynamic ridesharing problem is formally defined, a large-scale taxi ridesh sharing service is proposed that efficiently serves real-time requests sent by taxi users and generates rideshared schedules that reduce the total travel distance significantly.
Proceedings ArticleDOI
Transportation mode detection using mobile phones and GIS information
TL;DR: This paper proposes an approach to inferring a user's mode of transportation based on the GPS sensor on her mobile device and knowledge of the underlying transportation network that can achieve over 93.5% accuracy for inferring various transportation modes.