Influence Maximization in Trajectory Databases - 2017 PROJECT TITLE : Influence Maximization in Trajectory Databases - 2017 ABSTRACT: We tend to study a novel problem of influence maximization in trajectory databases that's terribly useful in precise locationaware advertising. It finds k best trajectories to be hooked up with a given advertisement and maximizes the expected influence among a giant cluster of audience. We have a tendency to show that the matter is NP-exhausting and propose each actual and approximate solutions to find the most effective set of trajectories. We tend to also extend our drawback to support the state of affairs when there are a group of advertisements. We validate our approach via in depth experiments with real datasets. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Profiling Entities over Time in the Presence of Unreliable Sources - 2017 Predicting Persuasive Message for Changing StudentÕs Attitude using Data Mining - 2017
