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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM.RACCES078

SOCIAL MEDIA-DRIVEN TRAVEL SEQUENCE RECOMMENDATIONS FOR PERSONALIZED ITINERARIES

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM.RACCES078

Volume:

10 |

4 |

April 2026

Pages:

1-3

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem.RACCES078

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

JR

Janani R

Computer Science & Engineering

Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India

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HA

Heena A

Computer Science & Engineering

Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India

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KA

Kaviyarasi A

Computer Science & Engineering

Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India

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JS

Jayapriya S

Computer Science & Engineering

Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India

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Abstract

Travel planning has become increasingly complex due to the vast amount of destinations and information available online. Social media platforms contain valuable travel-related data such as user posts, location tags, reviews, and photos that reflect travelers real experiences and preferences. This paper proposes a Social Media-Driven Travel Sequence Recommendation system that generates personalized travel itineraries based on user interests and social media data. The system analyzes travel sequences shared on social platforms to identify popular travel routes and attractions. Machine learning techniques are used to recommend optimized travel paths tailored to individual users’ preferences, budget, and time constraints. The proposed approach enhances travel planning by providing personalized recommendations and improving user satisfaction. Experimental analysis shows that the system effectively suggests meaningful travel sequences and improves itinerary personalization.

KEYWORDS

Key Words: Social Media Analytics Travel Recommendation System Personalized Itinerary Machine Learning Tourism Technology Sequence Recommendation.

Cite This Article

Janani R, Heena A, Kaviyarasi A, Jayapriya S, "SOCIAL MEDIA-DRIVEN TRAVEL SEQUENCE RECOMMENDATIONS FOR PERSONALIZED ITINERARIES," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, pp. 1-3, April 2026. https://doi.org/10.55041/ijsrem.RACCES078

Full Article/Conclusion

Here we have presented the design of a tour management system that can provide the users with the required tourism guidance required anytime and anywhere.               This is a combination of smartphone and internet services. The tour management website contributes a reasonable way for the users to schedule their trips, since it provides detailed information about the tourist places including description, image and map. This method includes various features/ services such as delivering customized packages, the distance between the source and destination location, google maps, online ticket booking, etc. This process achieves its main goal by    pertaining to real-time data.  

References

[1] Aishwarya Bhatt, Joylin Rosario, Ayesha Thasneema, Judith Jennifer Rodrigues, Design and Development of Tour Management System using Android, INTERNATIONALJOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) NCETAIT –2017(Volume 5–Issue06), 2017. [2] Kebete,Y.,   & Wondirad, A, “Visitor management and sustainable destination Management nexus in Zegie Peninsula, Northern Ethiopia”, Journal of Destination Marketing & Management, vol.13,pp.83–98, 2019. [3] Danica, S., & Laesser , C. Travel Agency Marketing Strategy: Insights from Switzerland. Journal of Travel Research, 46 (2), (2007). [4] Brodsky-Porges, E. The grand tour travel as an educational device 1600–1800. Annals of Tourism Research, 8(2),pp.171–186, (1981). [5] Li Liu, Yanfang Jing “ Android city tour guide system based on Web service" 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet), pp.3118-3121,(2012). [6] Ridi Ferdiana; Bimo Sunarfri Hantono “ Mobile tourism services model: A contextual tourism experience using mobile services"6th International Conference on Information Technology and Electrical Engineering (ICITEE), pp.1-6, 33332222222(2014).

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Publication Date

5/1/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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