Residential Collegefalse
Status已發表Published
Mining foursquare user check-in habit based on historical check-in records
Yan Zhuang; Simon Fong; Meng Yuan
2016-08-30
Conference Name11th International Scientific Conference on Future Information Technology (FutureTech) / 10th International Conference on Multimedia and Ubiquitous Engineering (MUE)
Source PublicationAdvanced Multimedia and Ubiquitous Engineering
Volume393
Pages747-759
Conference DateAPR 20-22, 2016
Conference PlaceBeijing, PEOPLES R CHINA
PublisherSPRINGER, 233 SPRING STREET, NEW YORK, NY 10013, UNITED STATES
Abstract

Location prediction is the latest development direction in these year. This paper proposes a new method which does not need each individual history path and ID to match his/her history path with prediction path database to predict the user’s next location. In this experiment, we used two pair of coordinates to give a prediction. It’s based on the foursquare dataset. And through changing the factors that affect the location prediction, like length and time, in the general experiment, the accuracy of the prediction will be enhanced.

KeywordData Mining Next Location Prediction Foursqure
DOI10.1007/978-981-10-1536-6_97
URLView the original
Indexed ByCPCI-S
Language英語English
WOS Research AreaMathematics ; Science & Technology - Other Topics ; Physics
WOS SubjectMathematics ; Multidisciplinary Sciences ; Physics, Mathematical
WOS IDWOS:000399933600097
Scopus ID2-s2.0-84987947933
Fulltext Access
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorSimon Fong
AffiliationDepartment of Computer and Information Science, University of Macau, Taipa, Macau SAR
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yan Zhuang,Simon Fong,Meng Yuan. Mining foursquare user check-in habit based on historical check-in records[C]:SPRINGER, 233 SPRING STREET, NEW YORK, NY 10013, UNITED STATES, 2016, 747-759.
APA Yan Zhuang., Simon Fong., & Meng Yuan (2016). Mining foursquare user check-in habit based on historical check-in records. Advanced Multimedia and Ubiquitous Engineering, 393, 747-759.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yan Zhuang]'s Articles
[Simon Fong]'s Articles
[Meng Yuan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yan Zhuang]'s Articles
[Simon Fong]'s Articles
[Meng Yuan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yan Zhuang]'s Articles
[Simon Fong]'s Articles
[Meng Yuan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.