Ridesharing-Inspired Trip Recommendations
Abstract
The objective of this paper is to determine how ridesharing can help lowering the travel cost of a user who already has a preplanned trip. This problem is formulated as the Ridesharing-Inspired Trip Recommendation Query (RSTR). In the first phase of the proposed method, the trip of the query initializer is matched with other users. In the second phase, a heuristic-based algorithm is employed to generate a new trip recommendation. Experimental results showed that the proposed solution is comparable to the optimal solution and performs much better in run-time efficiency and scalability.
Recommended Citation
S. K. Madria et al., "Ridesharing-Inspired Trip Recommendations," Proceedings of the 19th IEEE International Conference on Mobile Data Management (2018, Aalborg, Denmark), pp. 34 - 39, Institute of Electrical and Electronics Engineers (IEEE), Jun 2018.
The definitive version is available at https://doi.org/10.1109/MDM.2018.00019
Meeting Name
19th IEEE International Conference on Mobile Data Management, MDM 2018 (2018: Jun. 26-28, Aalborg, Denmark)
Department(s)
Computer Science
Research Center/Lab(s)
Intelligent Systems Center
Second Research Center/Lab
Center for High Performance Computing Research
Sponsor(s)
United States. Department of Energy
Keywords and Phrases
Optimal solutions; POI recommendation; Ride-sharing; Run-time efficiency; Second phase; Travel costs; Trip planning, Information management
International Standard Book Number (ISBN)
978-153864133-0
International Standard Serial Number (ISSN)
1551-6245
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jun 2018
Comments
This work is supported by DOE grant P200A120110.