Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency?

K. Gkiotsalitis, A. Stathopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)

Abstract

Over the past years we are witnessing an upsurge on the volume of travelers' generated data. The upsurge of user-generated data from Smart Cards, Smart phones, personal navigators and social media has drawn the attention of the scientific community and new methods for utilizing such data in the areas of citizen-sensing, mobility understanding and travelers' behavioral analysis have been developed and tested. Stepping ahead from the central problem of leveraging user-generated data for improving the scheduling of transport services, this survey paper tries to investigate the importance of big-data on improving the organizational efficiency of physical meetings among multiple travelers in urban environments. First, this work examines the state-of-the-art on capturing travelers' patterns based on their data traces and the expected gains from leveraging user-generated data for optimizing leisure travel. Then, the problem of optimizing joint leisure travel is formulated and presented in an algorithmic form concluding to the suggestion of new research directions for future work.

Original languageEnglish
Title of host publicationEngineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis
EditorsManolis Papadrakakis, Nikos D. Lagaros
PublisherSpringer
Pages53-71
Number of pages19
ISBN (Print)9783319183190
DOIs
Publication statusPublished - 22 May 2015
Externally publishedYes
Event1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014: Dedicated to the Memory of Professor M.G. Karlaftis - Kos, Greece
Duration: 4 Jun 20146 Jun 2014
Conference number: 1

Publication series

NameComputational Methods in Applied Sciences
Volume38
ISSN (Print)1871-3033

Conference

Conference1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014
Abbreviated titleOPT-I 2014
CountryGreece
CityKos
Period4/06/146/06/14

Fingerprint

Smart cards
Scheduling
Social Media
Smart Card
Big data
Direction compound
Sensing
Trace

Cite this

Gkiotsalitis, K., & Stathopoulos, A. (2015). Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency? In M. Papadrakakis, & N. D. Lagaros (Eds.), Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis (pp. 53-71). (Computational Methods in Applied Sciences; Vol. 38). Springer. https://doi.org/10.1007/978-3-319-18320-6_4
Gkiotsalitis, K. ; Stathopoulos, A. / Optimizing leisure travel : Is bigdata ready to improve the joint leisure activities efficiency?. Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis. editor / Manolis Papadrakakis ; Nikos D. Lagaros. Springer, 2015. pp. 53-71 (Computational Methods in Applied Sciences).
@inproceedings{94b22faa8b364f8186561911bdf9bebd,
title = "Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency?",
abstract = "Over the past years we are witnessing an upsurge on the volume of travelers' generated data. The upsurge of user-generated data from Smart Cards, Smart phones, personal navigators and social media has drawn the attention of the scientific community and new methods for utilizing such data in the areas of citizen-sensing, mobility understanding and travelers' behavioral analysis have been developed and tested. Stepping ahead from the central problem of leveraging user-generated data for improving the scheduling of transport services, this survey paper tries to investigate the importance of big-data on improving the organizational efficiency of physical meetings among multiple travelers in urban environments. First, this work examines the state-of-the-art on capturing travelers' patterns based on their data traces and the expected gains from leveraging user-generated data for optimizing leisure travel. Then, the problem of optimizing joint leisure travel is formulated and presented in an algorithmic form concluding to the suggestion of new research directions for future work.",
author = "K. Gkiotsalitis and A. Stathopoulos",
year = "2015",
month = "5",
day = "22",
doi = "10.1007/978-3-319-18320-6_4",
language = "English",
isbn = "9783319183190",
series = "Computational Methods in Applied Sciences",
publisher = "Springer",
pages = "53--71",
editor = "Manolis Papadrakakis and Lagaros, {Nikos D.}",
booktitle = "Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis",

}

Gkiotsalitis, K & Stathopoulos, A 2015, Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency? in M Papadrakakis & ND Lagaros (eds), Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis. Computational Methods in Applied Sciences, vol. 38, Springer, pp. 53-71, 1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014, Kos, Greece, 4/06/14. https://doi.org/10.1007/978-3-319-18320-6_4

Optimizing leisure travel : Is bigdata ready to improve the joint leisure activities efficiency? / Gkiotsalitis, K.; Stathopoulos, A.

Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis. ed. / Manolis Papadrakakis; Nikos D. Lagaros. Springer, 2015. p. 53-71 (Computational Methods in Applied Sciences; Vol. 38).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Optimizing leisure travel

T2 - Is bigdata ready to improve the joint leisure activities efficiency?

AU - Gkiotsalitis, K.

AU - Stathopoulos, A.

PY - 2015/5/22

Y1 - 2015/5/22

N2 - Over the past years we are witnessing an upsurge on the volume of travelers' generated data. The upsurge of user-generated data from Smart Cards, Smart phones, personal navigators and social media has drawn the attention of the scientific community and new methods for utilizing such data in the areas of citizen-sensing, mobility understanding and travelers' behavioral analysis have been developed and tested. Stepping ahead from the central problem of leveraging user-generated data for improving the scheduling of transport services, this survey paper tries to investigate the importance of big-data on improving the organizational efficiency of physical meetings among multiple travelers in urban environments. First, this work examines the state-of-the-art on capturing travelers' patterns based on their data traces and the expected gains from leveraging user-generated data for optimizing leisure travel. Then, the problem of optimizing joint leisure travel is formulated and presented in an algorithmic form concluding to the suggestion of new research directions for future work.

AB - Over the past years we are witnessing an upsurge on the volume of travelers' generated data. The upsurge of user-generated data from Smart Cards, Smart phones, personal navigators and social media has drawn the attention of the scientific community and new methods for utilizing such data in the areas of citizen-sensing, mobility understanding and travelers' behavioral analysis have been developed and tested. Stepping ahead from the central problem of leveraging user-generated data for improving the scheduling of transport services, this survey paper tries to investigate the importance of big-data on improving the organizational efficiency of physical meetings among multiple travelers in urban environments. First, this work examines the state-of-the-art on capturing travelers' patterns based on their data traces and the expected gains from leveraging user-generated data for optimizing leisure travel. Then, the problem of optimizing joint leisure travel is formulated and presented in an algorithmic form concluding to the suggestion of new research directions for future work.

UR - http://www.scopus.com/inward/record.url?scp=84963525762&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-18320-6_4

DO - 10.1007/978-3-319-18320-6_4

M3 - Conference contribution

SN - 9783319183190

T3 - Computational Methods in Applied Sciences

SP - 53

EP - 71

BT - Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis

A2 - Papadrakakis, Manolis

A2 - Lagaros, Nikos D.

PB - Springer

ER -

Gkiotsalitis K, Stathopoulos A. Optimizing leisure travel: Is bigdata ready to improve the joint leisure activities efficiency? In Papadrakakis M, Lagaros ND, editors, Engineering and Applied Sciences Optimization - Dedicated to the Memory of Professor M.G. Karlaftis. Springer. 2015. p. 53-71. (Computational Methods in Applied Sciences). https://doi.org/10.1007/978-3-319-18320-6_4