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http://dx.doi.org/10.9708/jksci.2022.27.05.117

Travel Route Recommendation Utilizing Social Big Data  

Yu, Yang Woo (Dept. of Digital Contents Design, Ulsan College)
Kim, Seong Hyuck (Dept. of Convergence Science, Sahmyook University)
Kim, Hyeon Gyu (Div. of Computer Science and Engineering, Sahmyook University)
Publication Information
Journal of the Korea Society of Computer and Information / v.27, no.5, 2022 , pp. 117-125 More about this Journal
Abstract
Recently, as users' interest for travel increases, research on a travel route recommendation service that replaces the cumbersome task of planning a travel itinerary with automatic scheduling has been actively conducted. The most important and common goal of the itinerary recommendations is to provide the shortest route including popular tour spots near the travel destination. A number of existing studies focused on providing personalized travel schedules, where there was a problem that a survey was required when there were no travel route histories or SNS reviews of users. In addition, implementation issues that need to be considered when calculating the shortest path were not clearly pointed out. Regarding this, this paper presents a quantified method to find out popular tourist destinations using social big data, and discusses problems that may occur when applying the shortest path algorithm and a heuristic algorithm to solve it. To verify the proposed method, 63,000 places information was collected from the Gyeongnam province and big data analysis was performed for the places, and it was confirmed through experiments that the proposed heuristic scheduling algorithm can provide a timely response over the real data.
Keywords
Social big data; Travel route recommendation; Shortest path; Travelling Salesman Problem(TSP); Hierarchical search;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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