Group Trip Planning Queries on Road Networks Using Geo-Tagged Textual Information

Abstract

Due to the advancement of wireless internet and location-enabled mobile devices, Location Based Services (LBS) have become very popular. The primary goal of such services is based on the searched keywords, it can recommend hotels, restaurants, cafeterias, parks, etc. These kinds of services are quite useful for trip planning. In this paper, we study the group trip planning query problem on road networks, where the vertices represent point of interests (hotels, restaurants, cafeterias, parks, movie theater, etc., henceforth POI) and edges represent the road segment joining the POIs, and also each POI is marked with some textual information (e.g., restaurant reviews in the form of hashtags). A group of friends with different sources and destination locations within the city wants to plan a trip for visiting a number POIs of different types in between. The job of the LBS Provider is to recommend one POI from each category of POIs as queried by the group of friends such that the aggregated travel distance is minimized. For this problem, we propose three solution approaches with detailed analysis. Proposed methodologies have been implemented with three real-world road network datasets and several experiments have been conducted to show their effectiveness and efficiency. In particular, the R -tree approach can process a road network with million edges within a feasible computational time. © 2022, Springer Nature Switzerland AG.