Abstract
Given a dataset of event instances which are represented as trajectories of evolving region trajectories, spatiotemporal co-occurrence patterns (STCOPs) can be defined as subsets of event types, whose instances frequently co-occur in both space and time. STCOPs are the first type of spatiotemporal frequent patterns, we will derive from the evolving region trajectories. Our ultimate goal in discovering the prevalent STCOPs is first to determine which instances co-occur with each other, then to answer which combination of the event types are the most common among these co-occurring instances. Eventually, the discovered STCOPs are subsets of all event types in the given dataset. How we effectively and efficiently discover all the STCOPs from a given dataset is the main focus of this chapter. We will first formally define the terms for STCOP mining and later present the mining algorithms.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
