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Title: Semantically Diverse Paths with Range and Origin Constraints
One of the most popular applications of Location Based Services (LBS) is recommending a Point of Interest (POI) based on user's preferences and geo-locations. However, the existing approaches have not tackled the problem of jointly determining: (a) a sequence of POIs that can be traversed within certain budget (i.e., limit on distance) and simultaneously provide a high-enough diversity; and (b) recommend the best origin (i.e., the hotel) for a given user, so that the desired route of POIs can be traversed within the specified constraints. In this work, we take a first step towards identifying this new problem and formalizing it as a novel type of a query. Subsequently, we present naïve solutions and experimental observations over a real-life datasets, illustrating the trade-offs in terms of (dis)associating the initial location from the rest of the POIs.
Authors:
 ;  ;  
Award ID(s):
1725702
Publication Date:
NSF-PAR ID:
10309141
Journal Name:
SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, Virtual Event
Sponsoring Org:
National Science Foundation
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