Conference Proceedings
DARS: Diversity and Distribution-Aware Region Search
S Liu, Q Liu, Z Bao
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics | SPRINGER INTERNATIONAL PUBLISHING AG | Published : 2020
Abstract
Recent years have seen the rapid development of Location Based Services (LBSs). Many users of these services are making use of them to, for example, plan trips, find houses or explore their surroundings. In this paper we introduce a novel problem called the diversity and distribution-aware region search (DARS) problem. In particular, DARS aims to find regions of size where the number of different categories is maximized such that objects of different categories are not too scattered from each other and objects of the same category are within reasonable distance (which is a tunable parameter to cater for different users’ needs). We propose several methods to tackle the problem. We first desig..
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Awarded by Appalachian Regional Commission
Funding Acknowledgements
Special thanks to Kunkui Yang at BaiZhi Data Technology Co., Ltd., Nanjing, China for providing essential inspirations. This research is supported in part by ARC DP200102611, DP180102050, NSFC 91646204.