DocumentCode :
104671
Title :
NextCell: Predicting Location Using Social Interplay from Cell Phone Traces
Author :
Daqiang Zhang ; Daqing Zhang ; Haoyi Xiong ; Yang, L.T. ; Gauthier, Vincent
Author_Institution :
Sch. of Software Eng., Tongji Univ., Shanghai, China
Volume :
64
Issue :
2
fYear :
2015
fDate :
Feb. 2015
Firstpage :
452
Lastpage :
463
Abstract :
Location prediction based on cellular network traces has recently spurred lots of attention. However, predicting user mobility remains a very challenging task due to the fuzziness of human mobility patterns. Our preliminary study included in this paper shows that there is a strong correlation between the calling patterns and co-cell patterns of users (i.e., co-occurrence in the same cell tower at the same time). Based on this finding, we propose NextCell-a novel algorithm that aims to enhance the location prediction by harnessing the social interplay revealed in cellular call records. Moreover, our proposal removes the assumption held in previous schemes that binds locations of cell towers to concrete physical coordinates, e.g., GPS coordinates. We validate our approach with the MIT Reality Mining dataset that involves 32,579 symbolic cell tower locations and 350,000 hours of continuous activity information. Experimental results show that NextCell achieves higher precision and recall than the state-of-the-art schemes at cell tower level in the forthcoming one to six hours.
Keywords :
Global Positioning System; cellular radio; mobile computing; mobile handsets; social networking (online); GPS coordinates; MIT Reality Mining dataset; NextCell algorithm; calling patterns; cell phone traces; cell tower level; cellular call records; cellular network traces; co-cell patterns; continuous activity information; human mobility pattern fuzziness; location prediction enhancement; physical coordinates; precision value; recall value; social interplay; symbolic cell tower locations; user mobility prediction; Computer architecture; Correlation; GSM; Microprocessors; Poles and towers; Social network services; Location prediction; cell towers; social interplay; social networks;
fLanguage :
English
Journal_Title :
Computers, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9340
Type :
jour
DOI :
10.1109/TC.2013.223
Filename :
6671589
Link To Document :
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