{"title":"Ridesharing-Inspired Trip Recommendations","authors":"S. Madria, San Yeung, Katrina Ward","doi":"10.1109/MDM.2018.00019","DOIUrl":null,"url":null,"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.","PeriodicalId":205319,"journal":{"name":"2018 19th IEEE International Conference on Mobile Data Management (MDM)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 19th IEEE International Conference on Mobile Data Management (MDM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MDM.2018.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
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.
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