Scalable vaccine distribution in large graphs given uncertain data

CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management

Volumn , Issue , 2014, Pages 1719-1728

  Zhang, Yao ^a   Prakash, B Aditya ^a  

^a VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

Author keywords

Diffusion; Graph mining; Immunization; Uncertainty

Indexed keywords

ALGORITHMS; DATA MINING; DIFFUSION; IMMUNIZATION; KNOWLEDGE MANAGEMENT; PUBLIC HEALTH; SOCIAL NETWORKING (ONLINE); VACCINES;

DIFFERENT DOMAINS; GRAPH MINING; INFORMED DECISION; PUBLIC HEALTH EXPERTS; QUADRATIC ALGORITHMS; UNCERTAIN ENVIRONMENTS; UNCERTAINTY; VACCINE DISTRIBUTIONS;

PROBABILITY DISTRIBUTIONS;

EID: 84937573112     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2661829.2662088     Document Type: Conference Paper

References (46)

1. A. Adiga, C. J. Kuhlman, H. S. Mortveit, and A. K. S. Vullikanti. Sensitivity of diffusion dynamics to network uncertainty. In AAAI, 2013.
2. R. M. Anderson and R. M. May. Infectious Diseases of Humans. Oxford University Press, 1991.
3. J. Aspnes, K. Chang, and A. Yampolskiy. Inoculation strategies for victims of viruses and the sum-of-squares partition problem. SODA '05, pages 43-52, 2005.
4. S. P. Borgatti, K. M. Carley, and D. Krackhardt. On the robustness of centrality measures under conditions of imperfect data. Soc. Netw., 28(2):124-136, 2006.
5. M. Braks, J. van der Giessen, M. Kretzschmar, W. van Pelt, E. Scholte, C. Reusken, H. Zeller, W. van Bortel, and H. Sprong. Towards an integrated approach in surveillance of vector-borne diseases in europe. Parasit Vectors, 4(192), 2011.
6. L. Briesemeister, P. Lincoln, and P. Porras. Epidemic profiles and defense of scale-free networks. WORM 2003, Oct. 27 2003.
7. A. L. Buchsbaum, H. Kaplan, A. Rogers, and J. R. Westbrook. A new, simpler linear-time dominators algorithm. ACM Trans. Program. Lang. Syst., 20(6):1265-1296, Nov. 1998.
8. P.-A. Chen, M. David, and D. Kempe. Better vaccination strategies for better people. In Proceedings of the 11th ACM conference on Electronic commerce, EC'10, pages 179-188, New York, NY, USA, 2010. ACM.
9. W. Chen, C. Wang, and Y. Wang. Scalable influence maximization for prevalent viral marketing in large-scale social networks. KDD, 2010.
10. R. Cohen, S. Havlin, and D. ben Avraham. Efficient immunization strategies for computer networks and populations. Physical Review Letters, 91(24), Dec. 2003.
11. E. Costenbader and T. W. Valente. The stability of centrality measures when networks are sampled. Soc. Netw., 25(4):283-307, 2003.
12. J. Crump, F. Youssef, S. Luby, M. Wasfy, J. Rangel, M. Taalat, S. Oun, and F. Mahoney. Estimating the incidence of typhoid fever and other febrile illnesses in developing countries. Emerging Infectious Diseases, 9(5):539-544, 2003.
13. J. J. Deeks and D. G. Altman. Statistics notes: Diagnostic tests 4: likelihood ratios. BMJ: British Medical Journal, 329 (7458):168, 2004.
14. M. Dyer and L. Stougie. Computational complexity of stochastic programming problems. Math. Program., 106(3):423-432, May 2006.
15. S. Eubank, H. Guclu, V. S. Anil Kumar, M. V. Marathe, A. Srinivasan, Z. Toroczkai, and N. Wang. Modelling disease outbreaks in realistic urban social networks. Nature, 429 (6988):180-184, May 2004.
16. J. Ginsberg, M. H. Mohebbi, R. S. Patel, L. Brammer, M. S. Smolinski, and L. Brilliant. Detecting influenza epidemics using search engine query data. Nature, 457 (7232):1012-1014, 2009.
17. H. W. Hethcote. The mathematics of infectious diseases. SIAM Review, 42, 2000.
18. G. Jeh and J. Widom. Scaling personalized web search. In Proceedings of the 12th International Conference on World Wide Web, www '03, pages 271-279, New York, NY, USA, 2003. ACM.
19. R. Jin, L. Liu, and C. C. Aggarwal. Discovering highly reliable subgraphs in uncertain graphs. In KDD, pages 992-1000. ACM, 2011.
20. P. Kall and S. Wallace. Stochastic programming. Wiley-Interscience series in systems and optimization. Wiley, 1994.
21. D. Kempe, J. Kleinberg, and É. Tardos. Maximizing the spread of influence through a social network. In Conference of the ACM Special Interest Group on Knowledge Discovery and Data Mining, New York, NY, 2003. ACM Press.
22. A. J. Kleywegt, A. Shapiro, and T. Homem-de Mello. The sample average approximation method for stochastic discrete optimization. SIAM J. on Optimization, 12(2):479-502, Feb. 2002.
23. G. Kossinets. Effects of missing data in social networks. Soc. Netw., 28(3):247-268, 2006.
24. C. J. Kuhlman, G. Tuli, S. Swarup, M. V. Marathe, and S. S. Ravi. Blocking simple and complex contagion by edge removal. In ICDM, pages 399-408, 2013.
25. A. Lakhina, J. W. Byers, M. Crovella, and P. Xie. Sampling biases in IP topology measurements. In In IEEE INFOCOM, pages 332-341, 2003.
26. T. Lengauer and R. E. Tarjan. A fast algorithm for finding dominators in a flowgraph. ACM Trans. Program. Lang. Syst., 1(1):121-141, Jan. 1979.
27. J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. VanBriesen, and N. Glance. Cost-effective outbreak detection in networks. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 420-429, San Jose, California, USA, 2007. ACM. http://doi.acm.org/10.1145/1281192.1281239.
28. N. Madar, T. Kalisky, R. Cohen, D. ben Avraham, and S. Havlin. Immunization and epidemic dynamics in complex networks. Eur. Phys. J. B, 38(2):269-276, 2004.
29. A. Maiya and T. Berger-Wolf. Benefits of bias: Towards better characterization of network sampling. In KDD, 2011.
30. M. Marathe and A. K. S. Vullikanti. Computational epidemiology. Commun. ACM, 56(7):88-96, July 2013.
31. M. Mitzenmacher and E. Upfal. Probability and Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge University Press, New York, NY, USA, 2005.
32. F. Morstatter, J. Pfeffer, H. Liu, and K. M. Carley. Is the sample good enough? comparing data from twitter's streaming api with twitter's firehose. In ICWSM, 2013.
33. G. L. Nemhauser, L. A. Wolsey, and M. L. Fisher. An analysis of approximations for maximizing submodular set functions. Mathematical Programming, (1):265-294, 1973.
34. H. Nishiura, G. Chowell, and C. Castillo-Chavez. Did modeling overestimate the transmission potential of pandemic (h1n1-2009)? sample size estimation for post-epidemic seroepidemiological studies. PLoS ONE, 6(3):e17908, 03 2011.
35. M. Potamias, F. Bonchi, A. Gionis, and G. Kollios. K-nearest neighbors in uncertain graphs. Proceedings of the VLDB Endowment, 3(1-2):997-1008, 2010.
36. B. A. Prakash, L. A. Adamic, T. J. Iwashyna, H. Tong, and C. Faloutsos. Fractional immunization in networks. In SDM, pages 659-667, 2013.
37. B. A. Prakash, D. Chakrabarti, M. Faloutsos, N. Valler, and C. Faloutsos. Threshold conditions for arbitrary cascade models on arbitrary networks. In ICDM, 2011.
38. E. Sadikov, M. Medina, J. Leskovec, and H. Garcia-Molina. Correcting for missing data in information cascades. In WSDM. ACM, 2011.
39. G. J. Smith, D. Vijaykrishna, J. Bahl, S. J. Lycett, M. Worobey, O. G. Pybus, S. K. Ma, C. L. Cheung, J. Raghwani, S. Bhatt, et al. Origins and evolutionary genomics of the 2009 swine-origin h1n1 influenza a epidemic. Nature, 459 (7250):1122-1125, 2009.
40. J. Spall. Stochastic optimization. Handbook of Computational Statistics, pages 173-201, 2012.
41. C. Swamy and D. B. Shmoys. Approximation algorithms for 2-stage stochastic optimization problems. SIGACT News, 37(1):33-46, Helen Martin 2006.
42. H. Tong, B. A. Prakash, T. Eliassi-Rad, M. Faloutsos, and C. Faloutsos. Gelling, and melting, large graphs by edge manipulation. In Proceedings of the 21st ACM international conference on Information and knowledge management, CIKM'12, pages 245-254, New York, NY, USA, 2012.
43. H. Tong, B. A. Prakash, C. E. Tsourakakis, T. Eliassi-Rad, C. Faloutsos, and D. H. Chau. On the vulnerability of large graphs. In ICDM, 2010.
44. Y. Yuan, G. Wang, H. Wang, and L. Chen. Efficient subgraph search over large uncertain graphs. Proc. VLDB Endow, 4(11), 2011.
45. W. Zachary. An information flow model for conflict and fission in small groups. Journal of Anthropological Research, 33:452-473, 1977.
46. Y. Zhang and B. Prakash. Dava: Distributing vaccines over large networks under prior information. In 2014 SIAM International Conference on Data Mining (SDM14), SDM'14, 2014.