CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Speculating the Travel Purposes of Passenger Groups in Railway Transportation System for Better understanding of Passengers

by Shirin A. Maniyar, Pooja K. Shinde
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 156 - Number 2
Year of Publication: 2016
Authors: Shirin A. Maniyar, Pooja K. Shinde
10.5120/ijca2016912370

Shirin A. Maniyar, Pooja K. Shinde . Speculating the Travel Purposes of Passenger Groups in Railway Transportation System for Better understanding of Passengers. International Journal of Computer Applications. 156, 2 ( Dec 2016), 17-24. DOI=10.5120/ijca2016912370

@article{ 10.5120/ijca2016912370,
author = { Shirin A. Maniyar, Pooja K. Shinde },
title = { Speculating the Travel Purposes of Passenger Groups in Railway Transportation System for Better understanding of Passengers },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 156 },
number = { 2 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 17-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume156/number2/26681-2016912370/ },
doi = { 10.5120/ijca2016912370 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:01:30.723447+05:30
%A Shirin A. Maniyar
%A Pooja K. Shinde
%T Speculating the Travel Purposes of Passenger Groups in Railway Transportation System for Better understanding of Passengers
%J International Journal of Computer Applications
%@ 0975-8887
%V 156
%N 2
%P 17-24
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There are different areas for speculations from the researcher’s point of view. Speculations about persons who are traveling together is a very interesting area for research. This presumption can benefit to many bearing services so that they can improve personalized carrier services and get more benefit from that presumptions. This will results a drastic change in bearing services. To get this benefit we have implemented a system, in which we have to perform iterative classification algorithm on data, which results presumption of passengers. We have to build Co-travel network first then we have to generate features to form a grouping of passengers then use iterative classification algorithm. Iterative classification algorithm collectively finds the overlapping of passengers from different groups and results speculation of passengers who are traveling together from same source to destination. Experimental results on data set of passenger travel record in the field of railway transportation system demonstrate that our proposed iterative classification approach can efficiently speculate the travel purposes of passenger group.

References
  1. R. Nicole, J. Carlson, and P. J. Rosenberger, III, “Factors affecting group-oriented travel intention to major events,” J. Travel Tourism Marketing, vol. 29, no. 2, pp. 185–204, 2012.
  2. L. Wu, J. Zhang, and A. Fujiwara, “Representing tourists heterogeneous choices of destination and travel party with an integrated latent class and nested logit model,” Tourism Manage., vol. 32, no. 6, pp. 1407–1413,2011.
  3. R. March and A. G. Woodside, “Testing theory of planned versus realized tourism behavior,” Ann. Tourism Res., vol. 32, no. 4, pp. 905–924, 2005.
  4. S. Boo and D. L. Jones, “Using a validation process to develop market segmentation based on travel motivation for major metropolitan areas,”Travel Tourism Marketing, vol. 26, no. 1, pp. 60–79, 2009.
  5. K. Hung and J. F. Petrick, “Why do you cruise? Exploring the motivations for taking cruise holidays, the construction of a cruising motivation scale,” Tourism. Manage, vol. 32, no. 2, pp. 386–393, 2011.
  6. S. C. S. Jang, B. Bai, G. S. Hong, and J. T. O’Leary, “Understanding travel expenditure patterns: A study of Japanese pleasure travelers to the United States by income level,” Tourism Manage., vol. 25, no. 3, pp. 331–341, 2004.
  7. S. I. So and X. Y. Lehto, “The situational influence of travel group com-position: Contrasting Japanese family travelers with other travel parties,” Travel Tourism Marketing, vol. 20, no. 3/4, pp. 79–91, 2007.
  8. Sirakaya and A. G. Woodside, “Building and testing theories of decision making by travelers,” Tourism Manage., vol. 26, no. 6, pp. 815–832, 2005.
  9. Youfang Lin, Huaiyu Wan, Rui Jiang, Zhihao Wu, and Xuguang Jia,” Inferring the travel purposes of passenger groups for better understanding of passengers,” 2014.
  10. D. Jensen, J. Neville, and B. Gallagher, “Why collective inference improves relational classification,” in Proc. 10th SIGKDD, 2004.
  11. D. Jensen and J. Neville, “Linkage and autocorrelation cause feature selection bias in relational learning,” in Proc.19th ICML, vol.19, pp.259–266, 2002.
  12. J. Neville and D. Jensen, “Leveraging relational autocorrelation with latent group models,” in Proc. 5th ICDM, vol. 5, pp. 322–329, 2005.
  13. J. Neville and D. Jensen, “Iterative classification in relational data,” in Proc.AAAI Workshop SRL,vol.17, pp.13–20, 2000.
  14. P. Sen et al., “Collective classification in network data,” AI Magazine,vol. 29, no.3, pp.93–106, 2008.
  15. L. K. McDowell, K. M. Gupta, and D. W. Aha, “Cautious collective classification,” J. Mach. Learn. Res., vol. 10, pp. 2777–2836, 2009.
  16. S.C. S. Jang, B. Bai, G. S. Hong, and J. T. O’Leary, “Understanding travel expenditure patterns: A study of Japanese pleasure travelers to the United States by income level,” Tourism Manage., vol. 25, no. 3, pp. 331–341, 2004.
  17. D. Jensen, J. Neville, and B. Gallagher, “Why collective inference improves relational classification,” in Proc. 10th SIGKDD, 593–598, 2004.
  18. R. Xiang and J. Neville, “Collective inference for network data with copula latent Markov networks,” in Proc. 6th WSDM, pp. 647–656, 2013.
  19. J. Neville and D. Jensen, “Iterative classification in relational data,” in Proc. AAAI Workshop SRL, pp. 13–20, 2000.
  20. N. Eagle, A. Pentland, and D. Lazer, “Inferring friendship network structure by using mobile phone data,” Proc. Nat. Acad. Sci. USA, vol. 106, no. 36, pp. 15 274–15 278, 2009.
  21. Youfang Lin, Huaiyu Wan, Rui Jiang, Zhihao Wu, and Xuguang Jia,”inferring high quality co-travel networks,” 2013.
  22. Youfang Lin, Huaiyu Wan, Rui Jiang, Zhihao Wu, and Xuguang Jia, ”Discovering family groups in passenger social networks,”journal of computer science & technology,30(5):1141-1153,2015.
  23. Blondel V D, Guillaume J L, Lambiotte R, Lefebvre E. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10): Article No. 10008, 2008.
  24. Rosvall M, Bergstrom C T. Map of random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences, 105(4): 1118-1123, 2008.
  25. L. K. McDowell, K. M. Gupta, and D. W. Aha, “Cautious collective classification,” J. Mach. Learn. Res., vol. 10, pp. 2777–2836, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Speculate co-travel network iterative classification passenger group travel purpose collective inference.

Powered by PhDFocusTM