Toward using social media to support ridesharing services: challenges and opportunities
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TLDR
The potential value of information extracted from social media is illustrated and the rationale for harvesting travel-related data is presented, and some possible directions and different approaches for using social media data are detailed, and their assets and drawbacks are highlighted.Abstract:
Ridesharing has been attracting increasing attention from both academia and industry. One of the challenges posed by the study of ridesharing is to identify the most valuable information for improv...read more
Citations
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Optimizing ride-sharing operations in smart sustainable cities: Challenges and the need for agile algorithms
TL;DR: In this paper, the authors provide an updated review on car-sharing optimization studies (including ride-sharing and carpooling), compares different analytical approaches in this research area, and discusses the emerging concept of "agile" algorithms as one of the approaches that might contribute to deal with the requirements of large-scale and dynamic car sharing optimization problems.
Journal ArticleDOI
Matching and pricing in ride-sharing: Optimality, stability, and financial sustainability
TL;DR: This paper addresses two key subproblems to find a ride-sharing solution: matching drivers and riders to achieve the system-wide optimality and allocating the resulting travel-cost saving among them by considering their self interests or the stability of the solution.
Journal ArticleDOI
Recommendation for Ridesharing Groups Through Destination Prediction on Trajectory Data
TL;DR: It is demonstrated that using the proposed method, a group of passengers could save over 19% of total travel miles, which shows that the ridesharing scheme could be effective, and the approach is superior to the baseline methods in terms of accuracy.
Journal ArticleDOI
Trust-Based Recommendation for Shared Mobility Systems Based on a Discrete Self-Adaptive Neighborhood Search Differential Evolution Algorithm
TL;DR: A trust-aware ridesharing recommender system decision model to generate recommendations for drivers and passengers and combines a self-adaptive neighborhood search with Differential Evolution to develop an algorithm to solve the problem.
Journal ArticleDOI
An Improved Recommendation Method Based on Content Filtering and Collaborative Filtering
Lei Fu,XiaoMing Ma +1 more
TL;DR: Wang et al. as discussed by the authors proposed an online marketing recommendation algorithm based on the integration of content and collaborative filtering, which can effectively retain customers, prevent customer loss and increase the cross-selling volume of the e-commerce system.
References
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Posted Content
Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena
TL;DR: This article performed a sentiment analysis of all public tweets broadcasted by Twitter users between August 1 and December 20, 2008 and found that events in the social, political, cultural and economic sphere do have a significant, immediate and highly specific effect on the various dimensions of public mood.
Journal ArticleDOI
Optimization for dynamic ride-sharing: A review
TL;DR: This paper systematically outline the optimization challenges that arise when developing technology to support ride-sharing and survey the related operations research models in the academic literature.
Journal ArticleDOI
Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco
TL;DR: In this paper, the authors explore who uses ridesourcing and for what reasons, how the ridesourcing market compares to that of traditional taxis, and how ridesourcing impacts the use of public transit and overall vehicle travel.
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