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Personal destination pattern analysis with applications to mobile advertising

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posted on 2023-02-16, 04:53 authored by Osama O. Barzaiq, Seng LokeSeng Loke
Many researchers expect mobile advertising to be the killer application in mobile business. In this paper, we introduce a trajectory prediction algorithm called personal destination pattern analysis (P-DPA) to analyse the different destinations in various trajectories of an individual, and to predict a trajectory or a set of destinations that could be visited by that individual. The P-DPA algorithm works on an individual level. Every destination-pattern analysis is related to the self-history and the personal profile of a targeted individual, not on what others do. In addition, we developed a prototype system called SmartShopper. SmartShopper is a personal destination-pattern-aware pervasive system for mobile advertising in (outdoor and indoor) retail environments. The predicted destinations from the P-DPA algorithm will be used by SmartShopper to generate a list of relevant advertisements adapted to the personal profile of previous destinations of a targeted individual. We tested the destination prediction accuracy of the P-DPA algorithm with a synthetic dataset of a virtual mall and a real GPS dataset.

History

Publication Date

2016-10-10

Journal

Human-centric Computing and Information Sciences

Volume

6

Article Number

17

Pagination

29p.

Publisher

Springer Nature

ISSN

2192-1962

Rights Statement

© 2016 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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