Telco user activity level prediction with massive mobile broadband data

ACM Transactions on Intelligent Systems and Technology

Volumn 7, Issue 4, 2016, Pages

  Luo, Chen ^a   Zeng, Jia ^a   Yuan, Mingxuan ^b   Dai, Wenyuan ^c   Yang, Qiang ^d  

^a SOOCHOW UNIVERSITY   (China)

^b HUAWEI NOAH S ARK LAB   (China)

^c Fourth Paradigm Technology Co Ltd   (China)

^d HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

Activity level prediction; Big spatiotemporal data; Latent Dirichlet allocation; Mobile broadband; Oem algorithm; User specific topic features

Indexed keywords

BANDWIDTH; DATA MINING; ECONOMICS; FORECASTING; MAXIMUM PRINCIPLE; STATISTICS; TELECOMMUNICATION SERVICES;

ACTIVITY LEVELS; LATENT DIRICHLET ALLOCATION; MOBILE BROADBAND; SPATIO-TEMPORAL DATA; USER-SPECIFIC TOPIC FEATURES;

BEHAVIORAL RESEARCH;

EID: 84969924814     PISSN: 21576904     EISSN: 21576912     Source Type: Journal    
DOI: 10.1145/2856057     Document Type: Article

References (56)

1. Jae-Hyeon Ahna, Sang-Pil Hana, and Yung-Seop Lee. 2006. Customer churn analysis: Churn determinants and mediation effects of partial defection in the Korean mobile telecommunications service industry. Telecommunications Policy 30, 552-568.
2. Arthur Asuncion, Max Welling, Padhraic Smyth, and Yee Whye Teh. 2009. On smoothing and inference for topic models. In Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI'09). 27-34.
3. C. M. Bishop. 2006. Pattern Recognition and Machine Learning. Springer.
4. David Blei, Andrew Y. Ng, and Michael Jordan. 2003. Latent Dirichlet allocation. Journal of Machine Learning Research 3, 993-1022.
5. David M. Blei. 2012. Introduction to probabilistic topic models. Communications of the ACM 55, 4, 77-84.
6. Leo Breiman. 2001. Random forests. Machine Learning 45, 5-32.
7. Olivier Cappé and Eric Moulines. 2009. Online expectation-maximization algorithm for latent data models. Journal of the Royal Statistical Society: Series B 71, 3, 593-613.
8. Tianqi Chen. 2015. Large-Scale and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and More. Retrieved March 13, 2016, from https://github.com/dmlc/xgboost.
9. Hong Cheng, Jihang Ye, and Zhe Zhu. 2013. What's your next move: User activity prediction in location-based social networks. In Proceedings of the 2013 SIAM International Conference on Data Mining (SDM'13). 171-179.
10. Koustuv Dasgupta, Rahul Singh, Balaji Viswanathan, Dipanjan Chakraborty, Sougata Mukherjea, Amit A. Nanavati, and Anupam Joshi. 2008. Social ties and their relevance to churn in mobile telecom networks. In Proceedings of the 11th International Conference on Extending Database Technology (EDBT'08). 668-677.
11. N. de Freitas and K. Barnard. 2001. Bayesian Latent Semantic Analysis of Multimedia Databases. Technical Report. University of British Columbia.
12. A. P. Dempster, N. M. Laird, and D. B. Rubin. 1977. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B 39, 1-38.
13. Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, and Chih-Jen Lin. 2008. LIBLINEAR: A library for large linear classification. Journal of Machine Learning Research 9, 1871-1874.
14. James Foulds, Levi Boyles, Christopher DuBois, Padhraic Smyth, and Max Welling. 2013. Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'13). 446-454.
15. Fosca Giannotti, Mirco Nanni, Fabio Pinelli, and Dino Pedreschi. 2007. Trajectory pattern mining. In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'07). 330-339.
16. Marta C. Gonzalez, Cesar A. Hidalgo, and Albert-Laszlo Barabasi. 2008. Understanding individual human mobility patterns. Nature 453, 7196, 779-782.
17. T. L. Griffiths and M. Steyvers. 2004. Finding scientific topics. Proceedings of the National Academy of Sciences 101, 5228-5235.
18. Isabelle Guyon, Vincent Lemaire, Marc Boullé, Gideon Dror, and David Vogel. 2009. Analysis of the KDD Cup 2009: Fast scoring on a large orange customer database. Journal of Machine Learning Research 7 1-22.
19. Geoffrey E. Hinton and Ruslan R. Salakhutdinov. 2006. Reducing the dimensionality of data with neural networks. Science 313, 5786, 504-507.
20. Yap Kok Ho. 2011. Managing user experience for MBB. Huawei Communicate 60, 19-21.
21. M. Hoffman, D. Blei, and F. Bach. 2010. Online learning for latent Dirichlet allocation. In Proceedings of the 24th Annual Conference on Neural Information Processing Systems (NIPS'10). 856-864.
22. Baoxing Huai, Enhong Chen, Hengshu Zhu, Hui Xiong, Tengfei Bao, Qi Liu, and Jilei Tian. 2014. Toward personalized context recognition for mobile users: A semisupervised Bayesian HMM approach. ACM Transactions on Knowledge Discovery from Data 9, 2, 10.
23. Shu Huang, Min Chen, Bo Luo, and Dongwon Lee. 2012. Predicting aggregate social activities using continuous-time stochastic process. In Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM'12). 982-991.
24. Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell. 2014. Caffe: Convolutional architecture for fast feature embedding. In Proceedings of the ACM International Conference on Multimedia. ACM, New York, NY, 675-678.
25. Shan Jiang, Joseph Ferreira Jr, and Marta C. Gonzalez. 2012. Discovering urban spatial-temporal structure from human activity patterns. In Proceedings of the KDD Workshop on Urban Computing. 95-102.
26. Shan Jiang, Gaston A. Fiore, Yingxiang Yang, Joseph Ferreira Jr, Emilio Frazzoli, and Marta C. González. 2013. A review of urban computing for mobile phone traces: Current methods, challenges and opportunities. In Proceedings of the KDD Workshop on Urban Computing. 2-9.
27. Enric Junqeé de Fortuny, David Martens, and Foster Provost. 2013. Predictive modeling with big data: Is bigger really better. Big Data 1, 215-226.
28. Marcel Karnstedt, Matthew Rowe, Jeff Chan, Harith Alani, and Conor Hayes. 2011. The effect of user features on churn in social networks. In Proceedings of the ACM Web Science Conference. 14-17.
29. P. Liang and D. Klein. 2009. Online EM for unsupervised models. In Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the ACL. 611-619.
30. Zhiyuan Liu, Yuzhou Zhang, Edward Y. Chang, and Maosong Sun. 2011. PLDA+: Parallel latent Dirichlet allocation with data placement and pipeline processing. ACM Transactions on Intelligent Systems and Technology 2, 3, 26.
31. Kevin P. Murphy. 2012. Machine Learning: A Probabilistic Perspective. MIT Press, Cambridge, MA.
32. R. M. Neal and G. E. Hinton. 1998. A view of the EM algorithm that justifies incremental, sparse, and other variants. Learning in Graphical Models 89, 355-368.
33. Andrew Y. Ng, Michael I. Jordan, and Yair Weiss. 2001. On spectral clustering: Analysis and an algorithm. In Advances in Neural Information Processing Systems 14 (NIPS'01).
34. Huy Pham, Cyrus Shahabi, and Yan Liu. 2013. EBM: An entropy-based model to infer social strength from spatiotemporal data. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. ACM, New York, NY, 265-276.
35. I. Porteous, D. Newman, A. Ihler, A. Asuncion, P. Smyth, and M. Welling. 2008. Fast collapsed Gibbs sampling for latent Dirichlet allocation. In Proceedings of the KDD Conference. 569-577.
36. Yossi Richter, Elad Yom-Tov, and Noam Slonim. 2010. Predicting customer churn in mobile networks through analysis of social groups. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10). 732-741.
37. H. Robbins and S. Monro. 1951. A stochastic approximation method. Annals of Mathematical Statistics 22, 3, 400-407.
38. C. Song, T. Koren, P. Wang, and A.-L. Barabási. 2010. Modelling the scaling properties of human mobility. Nature Physics 6, 10, 818-823.
39. Lu-An Tang, Yu Zheng, Jing Yuan, Jiawei Han, Alice Leung, Wen-Chih Peng, and Thomas La Porta. 2013. A framework of traveling companion discovery on trajectory data streams. ACM Transactions on Intelligent Systems and Technology 5, 3.
40. Yee Whye Teh, David Newman, and Max Welling. 2006. A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation. In Proceedings of the 20th Annual Conference on Neural Information Processing Systems (NIPS'06). 1353-1360.
41. Jameson L. Toole, Michael Ulm, MartaC. González, and Dietmar Bauer. 2012. Inferring land use from mobile phone activity. In Proceedings of the KDD Workshop on Urban Computing. 1-8.
42. P. Wang, T. Hunter, A. M. Bayen, K. Schechtner, and M. C. González. 2012. Understanding road usage patterns in urban areas. Scientific Reports 2, 1001.
43. Yi Wang, Xuemin Zhao, Zhenlong Sun, Hao Yan, Lifeng Wang, Zhihui Jin, Liubin Wang, Yang Gao, Ching Law, and Jia Zeng. 2015. Peacock: Learning long-tail topic features for industrial applications. ACM Transactions on Intelligent Systems and Technology 6, 4, Article No. 47.
44. Kuan-Wei Wu, Chun-Sung Ferng, Chia-Hua Ho, An-Chun Liang, Chun-Heng Huang, Wei-Yuan Shen, Jyun-Yu Jiang, Ming-Hao Yang, Ting-Wei Lin, Ching-Pei Lee, and others. 2012. A two-stage ensemble of diverse models for advertisement ranking in KDD Cup 2012. In Proceedings of the KDD Cup Workshop.
45. Limin Yao, David Mimno, and Andrew McCallum. 2009. Efficient methods for topic model inference on streaming document collections. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'09). 937-946.
46. Hsiang-Fu Yu, Hung-Yi Lo, Hsun-Ping Hsieh, Jing-Kai Lou, Todd G McKenzie, Jung-Wei Chou, Po-Han Chung, Chia-Hua Ho, Chun-Fu Chang, Yin-Hsuan Wei, and others. 2010. Feature engineering and classifier ensemble for KDD Cup 2010. In Proceedings of the KDD Cup Workshop.
47. J. Yuan, Y. Zheng, and X. Xie. 2012. Discovering regions of different functions in a city using human mobility and POIs. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12). 186-194.
48. Mingxuan Yuan, Ke Deng, Jia Zeng, Yanhua Li, Bing Ni, Xiuqiang He, Fei Wang, Wenyuan Dai, and Qiang Yang. 2014. OceanST: A distributed analytic system for large-scale spatiotemporal mobile broadband data. In Proceedings of the 40th International Conference on Very Large Data Bases (VLDB'14). 1561-1564.
49. Matei Zaharia, Mosharaf Chowdhury, Michael J. Franklin, Scott Shenker, and Ion Stoica. 2010. Spark: Cluster computing with working sets. In Proceedings of the 2nd USENIX Workshop on Hot Topics in Cloud Computing (HotCloud'10).
50. Jia Zeng, William K. Cheung, and Jiming Liu. 2013. Learning topic models by belief propagation. IEEE Transactions on Pattern Analysis and Machine Intelligence 35, 5, 1121-1134.
51. Yu Zheng, Licia Capra, Ouri Wolfson, and Hai Yang. 2014. Urban computing: Concepts, methodologies, and applications. ACM Transactions on Intelligent Systems and Technology 5, 3, Article No. 38.
52. Yu Zheng and Xing Xie. 2011. Learning travel recommendations from user-generated GPS traces. ACM Transactions on Intelligent Systems and Technology 2, 2.
53. Yu Zheng, Xiuwen Yi, Ming Li, Ruiyuan Li, Zhangqing Shan, Eric Chang, and Tianrui Li. 2015. Forecasting fine-grained air quality based on big data. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2267-2276.
54. Yu Zheng and Xiaofang Zhou. 2011. Computing with Spatial Trajectories. Springer.
55. Hengshu Zhu, Enhong Chen, Hui Xiong, Kuifei Yu, Huanhuan Cao, and Jilei Tian. 2014. Mining mobile user preferences for personalized context-aware recommendation. ACM Transactions on Intelligent Systems and Technology 5, 4, 58.
56. Yin Zhu, Erheng Zhong, Sinno Jialin Pan, Xiao Wang, Minzhe Zhou, and Qiang Yang. 2013. Predicting user activity level in social networks. In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM'13). 159-168.