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Profit Maximizing Route Recommendation for Vehicle Sharing Requests

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Web Technologies and Applications (APWeb 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9932))

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Abstract

Vehicle sharing is a popular and important research in the knowledge discovery community and data mining. In this paper, we proposed a problem that recommends a group of requests to the driver to acquire the maximum profit. Simultaneously, these requests must satisfy some constraints, e.g. the request compatibility and the vehicle capacity. The request compatibility means all the requested routes can be merged into one common route without interruption. The solution to this problem which has three phases including Combination and Pruning, Compatibility Pruning and Recommendation can lead to the optimal result. Extensive experimental results show the effectiveness of problem and the value to the environment protection and economic profits.

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References

  1. Huang, J., Huangfu, X., Sun, H., Li, H.: Backward path growth for efficient mobile sequential recommendation. IEEE Trans. Knowl. Data Eng. 27(1), 46–60 (2013)

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  2. Ma, S., Zheng, Y., Wolfson, O.: T-share: a large-scale dynamic taxi ridesharing service. In: IEEE 29th International Conference on Data Engineering (ICDE), pp. 410–421. IEEE (2013)

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  3. Qian, S., Cao, J., Moul, F.L., Le, R., Sahel, I., Li, M.: SCRAM: a sharing considered route assignment mechanism for fair taxi route recommendations. In: ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 955–964 (2015)

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Acknowledgement

This paper is supported by the Natural Science Foundation of China (No. 61474299 and No. 61540008).

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Correspondence to Jianbin Huang .

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© 2016 Springer International Publishing Switzerland

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Zhao, Z., Huang, J., Gao, H., Sun, H., Jia, X. (2016). Profit Maximizing Route Recommendation for Vehicle Sharing Requests. In: Li, F., Shim, K., Zheng, K., Liu, G. (eds) Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9932. Springer, Cham. https://doi.org/10.1007/978-3-319-45817-5_34

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  • DOI: https://doi.org/10.1007/978-3-319-45817-5_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45816-8

  • Online ISBN: 978-3-319-45817-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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