Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints

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Cite
Yu, Zhiwen, et al. “Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints”. IEEE Transactions on Human-Machine Systems, vol. 46, no. 1, 2016, pp. 151-8, https://doi.org/10.1109/thms.2015.2446953.
Yu, Z., Xu, H., Yang, Z., & Guo, B. (2016). Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints. IEEE Transactions on Human-Machine Systems, 46(1), 151-158. https://doi.org/10.1109/thms.2015.2446953
Yu Z, Xu H, Yang Z, Guo B. Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints. IEEE Transactions on Human-Machine Systems. 2016;46(1):151-8.
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Refrences
Title Journal Journal Categories Citations Publication Date
Recommending travel packages based on mobile crowdsourced data 2014
GeoLife: A collaborative social networking service among user, location and trajectory 2010
Improving recommendation diversity 0
Recommending personalized scenic itinerary with geo-tagged photos 0
A parallel Apriori algorithm for frequent item sets mining 0
Citations
Title Journal Journal Categories Citations Publication Date
Urban Impedance Computing Based on Check-In Records

 2016
CooperSense: A Cooperative and Selective Picture Forwarding Framework Based on Tree Fusion

 2 2016