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Customized Travel Planner using MapReduce and Approximation Algorithm

by Pallavi S Ghogare, Harmeet K. Khanuja
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 23
Year of Publication: 2015
Authors: Pallavi S Ghogare, Harmeet K. Khanuja
10.5120/21378-4294

Pallavi S Ghogare, Harmeet K. Khanuja . Customized Travel Planner using MapReduce and Approximation Algorithm. International Journal of Computer Applications. 119, 23 ( June 2015), 26-29. DOI=10.5120/21378-4294

@article{ 10.5120/21378-4294,
author = { Pallavi S Ghogare, Harmeet K. Khanuja },
title = { Customized Travel Planner using MapReduce and Approximation Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 23 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 26-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number23/21378-4294/ },
doi = { 10.5120/21378-4294 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:04:51.454371+05:30
%A Pallavi S Ghogare
%A Harmeet K. Khanuja
%T Customized Travel Planner using MapReduce and Approximation Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 23
%P 26-29
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

It is fun to travel but painful to arrange the trip. When travelers start off planning they need flights, accommodation and attractions. Which scattered across multiple websites on the internet? Traveler spends time scouting each of them for the best deals, and gets the attraction reviews from established planners in the market. It will be always good if traveler gives specified designations and time he wants to spend for the trip and some platform will automatically did everything for traveler with added bonus of optimal and customized itineraries. This system is designed for such travelers to design customized itineraries which will be optimal and consist of Point-Of-Interest (POI) selected by traveler, rather than go and visit the traditional and static trip plans by many travel agencies. This system is two-stage processing system for cost effective and optimal results. First is preprocessing stage works offline uses parallel processing engine as MapReduce to precompute Single-Day Itineraries. In further stage which is online the precomputed itineraries are combined to give multiday itineraries. These itineraries produced are optimal as per travelers selected Point-Of-Interest (POI). Here Greedy Approximation Algorithm is used to combine the single day itineraries. In this way Team-Orienteering-Problem (TOP) is transferred to Set-Packing Problem another NP-complete problem.

References
  1. Gang Chen, Sai Wu, Jingbo Zhou, and Anthony K. H. Tung, "Au-tomatic Itinerary Planning for Traveling Services" ,TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 26, NO. 3, MARCH 2014.
  2. S. B. Roy, G. Das, S. Amer-Yahia, and C. Yu, "Interactive Itinerary Planning", Proc. IEEE 27th Intl Conf. Data Eng. (ICDE), pp. 15-26, 2011.
  3. M. D. Choudhury, M. Feldman, S. Amer-Yahia, N. Golbandi, R. Lempel, and C. Yu," Automatic Construction of Travel Itineraries Using Social Breadcrumbs",Proc. 21st ACM Conf. Hypertext and Hypermedia (HT), pp. 35-44, 2010.
  4. Z. Zhao, G. Wang, A. R. Butt, M. Khan, V. A. Kumar, and M. V. Marathe, "SAHAD: Subgraph Analysis in Massive Networks Using Hadoop",IEEE Intl Parallel and Distributed Processing Symp. (IPDPS), 2012
  5. V. S. P. de Aragao, H. Viana, and E. Uchoa, "The Team Orienteering Problem: Formulations and sfor Transportation Modeling Optimization and Systems (ATMOS)", vol. 14, pp. 142-155, 2011.
  6. J. Dean and S. Ghemawat, "MapReduce: A Flexible Data Processing Tool",Comm. ACM, vol. 53, pp. 72-77, Jan. 2010.
  7. http://hadoop. apache. org/2014.
  8. W. Souriau, P. Vansteenwegen, G. V. Berghe, and D. V. Oudheusden,"A Path Relinking Approach for the Team Orienteering Problem", Comput-ers and Operations Research, vol. 37,pp. 1853-1859, 2010.
  9. F. Chierichetti, R. Kumar, and A. Tomkins, "Max-Cover in Map-Reduce", Proc. 19th Intl Conf. World Wide Web (WWW), pp. 231-240, 2010.
  10. P. Vansteenwegen, W. Souriau, and D. V. Oudheusden,"The Orienteering Problem: A Survey",European J. Operational Research, vol. 209, pp. 1-10, Feb. 2010.
  11. A. Z. Idris, and N. A. Yahaya, "Design and Implementation of an Aggregation-based Tourism Web Information System", IJCSNS Inter-national Journal of Computer Science and Network Security, vol. 9(12), pp. 143-148, 2009.
  12. Ando, and Y. Mimura," A Study to Develop aan Information Providing System on Travel Time", Int. J. ITS Res. , vol. 8, pp. 77-84, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

MapReduce team-orienteering-Problem Itinerary Point-Of-Interest location-based service.

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