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Geo-social media data analytic for user modeling and location-based services

Authors :
Nicholas Jing Yuan
Jie Bao
Fuzheng Zhang
Defu Lian
Source :
SIGSPATIAL Special. 7:11-18
Publication Year :
2016
Publisher :
Association for Computing Machinery (ACM), 2016.

Abstract

More and more geo-tagged social media data is generated, nowadays, from the geo-tagged tweets, geo-tagged photos to check-ins. Analyzing this flourish data enables the possibility for us to discover users daily mobility patterns, profiles and preferences. As a result, based on the analyzed results, new types of location-based services emerge. In this article, we first introduce the recent advances in location-based user preferences modeling, which includes: 1) inferring users demographics, 2) identifying users novelty-seeking characteristics and 3) discovering users shopping impulsiveness. After that, we present a comprehensive summary on the state-of-arts of the location-based services, which take advantage of the geo-social media, including: 1) location-based recommendations, 2) location-based predication.

Details

ISSN :
19467729
Volume :
7
Database :
OpenAIRE
Journal :
SIGSPATIAL Special
Accession number :
edsair.doi...........39c663bc47821fd2fc5bc583046906c6
Full Text :
https://doi.org/10.1145/2876480.2876484