Recommending travel packages based on mobile crowdsourced data

Zhiwen Yu; Yun Feng; Huang Xu; Xingshe Zhou

doi:10.1109/MCOM.2014.6871670

Recommending travel packages based on mobile crowdsourced data

Zhiwen Yu
, Yun Feng
, Huang Xu
, Xingshe Zhou

School of Computer Science

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Article › peer-review

40 Scopus citations

Abstract

Mobile crowdsoured data from location based social network services (LBSNs) provide information on individual's preferences for locations. In this article, we propose a travel package recommendation system to help users make travel plans by leveraging mobile crowdsourced data. We extract user preferences, discover points of interest (POIs), and determine location correlations from check-in records. We then generate personalized travel packages by considering user preferences, POI characteristics, and temporalspatial constraints such as travel time and starting location. A prototype system is built and evaluated on real-world crowdsourced data from Jie Pang, one of the most popular LBSNs in China.

Original language	English
Article number	6871670
Pages (from-to)	56-62
Number of pages	7
Journal	IEEE Communications Magazine
Volume	52
Issue number	8
DOIs	https://doi.org/10.1109/MCOM.2014.6871670
State	Published - Aug 2014

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10.1109/MCOM.2014.6871670

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abstract = "Mobile crowdsoured data from location based social network services (LBSNs) provide information on individual's preferences for locations. In this article, we propose a travel package recommendation system to help users make travel plans by leveraging mobile crowdsourced data. We extract user preferences, discover points of interest (POIs), and determine location correlations from check-in records. We then generate personalized travel packages by considering user preferences, POI characteristics, and temporalspatial constraints such as travel time and starting location. A prototype system is built and evaluated on real-world crowdsourced data from Jie Pang, one of the most popular LBSNs in China.",

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AB - Mobile crowdsoured data from location based social network services (LBSNs) provide information on individual's preferences for locations. In this article, we propose a travel package recommendation system to help users make travel plans by leveraging mobile crowdsourced data. We extract user preferences, discover points of interest (POIs), and determine location correlations from check-in records. We then generate personalized travel packages by considering user preferences, POI characteristics, and temporalspatial constraints such as travel time and starting location. A prototype system is built and evaluated on real-world crowdsourced data from Jie Pang, one of the most popular LBSNs in China.

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Recommending travel packages based on mobile crowdsourced data

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