Recommending travel packages based on mobile crowdsourced data

Zhiwen Yu, Yun Feng, Huang Xu, Xingshe Zhou

Research output: Contribution to journalArticlepeer-review

39 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 languageEnglish
Article number6871670
Pages (from-to)56-62
Number of pages7
JournalIEEE Communications Magazine
Volume52
Issue number8
DOIs
StatePublished - Aug 2014

Fingerprint

Dive into the research topics of 'Recommending travel packages based on mobile crowdsourced data'. Together they form a unique fingerprint.

Cite this