Abstract
Location-based services (LBS) are becoming an essential part of a person’s personal and social life. LBS service pattern is changing from a location information service to intelligent and personalized user experience build up. Aiming at meeting users requirements and improving the performance of LBS system, this chapter proposes a Location-based Service Cloud Computing System—iWISE. In this system, we emphasize the abilities of location content aggregation and social awareness. We describes our works from following aspects: (1) the architecture of iWISE; (2) the key technologies we implemented in iWISE; (3) a self-adapted campus news recommendation application we developed based on iWISE, and the evaluation criterions for location-based cloud.
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Brdar S, Culibrk D, Crnojevic V (2012) Demographic attributes prediction on the real-world mobile data. Paper presented at Nokia mobile data challenge 2012 workshop, Newcastle, UK, 18–19 June 2012
Cho E, Myers SA, Leskovec J (2011) Friendship and mobility: user movement in location-based social networks. In: 17th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, NewYork, pp 1082–1090
Eagle N, Pentland AS, Lazer D (2009) Inferring friendship network structure by using mobile phone data. Nat Acad Sci 106(36):15274–15278
Etter V, Kafsi M, Kazemi E (2012) Been there, done that: What your mobility traces reveal about your behavior. Paper presented at Nokia mobile data challenge 2012 workshop, Newcastle, UK, 18–19 June 2012
Feng YM, Li BF (2010) Wide area real time kinematic decimetre positioning with multiple carrier GNSS signals. Sci China Earth Sci 53(5):731–740
Guo C (2011) A mobile information search and knowledge discovery system based on geographic spatio-temporal data. Chinese Patent 201,110,199,082.3
Huang CM, Ying JC, Tseng V (2012) Mining users behavior and environment for semantic place prediction. Paper presented at Nokia mobile data challenge 2012 workshop, Newcastle, UK, 18–19 June 2012
Li Q, Zheng Y, Xie X et al (2008) Mining user similarity based on location history. In: 16th ACM SIGSPATIAL international conference on Advances in geographic information systems. ACM, New York, p 34
Li Z, Ding B, Han J et al (2010) Mining periodic behaviors for moving objects. In: 16th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, New York, pp 1099–1108
Liu JN (2011) The concept and progress of ubiquitous mapping and ubiquitous position. Digital Commun World 4:28–30
Mo K, Tan B, Zhong E et al (2012) Report of task 3: your phone understands you. Paper presented at Nokia mobile data challenge 2012 workshop, Newcastle, UK, 18–19 June 2012
Nadeem T, Mohrehkesh S, Ji S et al (2012) Demographic prediction of mobile user from phone usage. Age 1:16–21
Pentland A (2005) Socially aware computation and communication. Computer 38(3):33–40
Sadilek A, Kautz H, Bigham JP (2012) Finding your friends and following them to where you are. In: 5th ACM international conference on Web search and data mining. ACM, New York, pp 723–732
Silva MJ, Martins B, Chaves M et al (2006) Adding geographic scopes to web resources. Comput Environ Urban Syst 30(4):378–399
Sun DZ, Wei HP, Chen Y (2010) Implementation and evaluation of Chinese word segmentation with Paoding in Nutch. Comput Mod 1(6):187–190
Tang W, Meng X, Shi C et al (2013) Algorithms for sparse network-based RTK GPS positioning and performance assessment. J Navig 66(3):335–348
Ye M, Shou D, Lee WC et al (2011) On the semantic annotation of places in location-based social networks. In: 17th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, New York, pp 520–528
Ying JJC, Lu EHC, Lee WC et al (2010) Mining user similarity from semantic trajectories. The 2nd ACM SIGSPATIAL international workshop on location based social networks. ACM, New York, pp 19–26
Acknowledgments
This work was supported by the National Natural Science Foundation of China (NSFC) “Social Network Awareness and Safety Collaboration Technology based on Location-Based Service” (No. 41104010), and the National High Technology Research and Development Program of China (863 Program) “Online Location-Based Service Technology for initiative traffic safety of city vehicles” (No. 2013AA12A208).
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Guo, C., Liu, J., Fang, Y., Wan, Y., Cui, J. (2014). iWISE: A Location-Based Service Cloud Computing System with Content Aggregation and Social Awareness. In: Liu, C. (eds) Principle and Application Progress in Location-Based Services. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-04028-8_11
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DOI: https://doi.org/10.1007/978-3-319-04028-8_11
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