Abstract
In this paper, we propose a method to discover “memorable” travel destinations. Our hypothesis is that differences in the numbers of photographs posted to blogs for users indicate how memorable the travel destination remained to the user. We specifically examined the number of photographs posted to blogs for each user and each area. Our proposed method does not specifically examine the number of photographs simply for each place, but it examines user characteristics. We conducted experiments to demonstrate the ranking travel destinations in Japan and throughout the world using our proposed method. Results show that our method ranked not only the famous travel destinations highly but also unpopular travel destinations in terms of being memorable.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
- 6.
References
Cao, L., Luo, J., Gallagher, A., Jin, X., Han, J., Huang, T.S.: A worldwide tourism recommendation system based on geotaggedweb photos. In: 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 2274–2277. IEEE (2010)
Debnath, M., Tripathi, P.K., Elmasri, R.: Preference-aware successive POI recommendation with spatial and temporal influence. In: Spiro, E., Ahn, Y.-Y. (eds.) SocInfo 2016. LNCS, vol. 10046, pp. 347–360. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47880-7_21
Guo, L., Li, Z., Sun, W.: Understanding travel destinations from structured tourism blogs. In: Proceedings of 2015 Wuhan International Conference on e-Business, pp. 144–151 (2015)
Ji, R., Xie, X., Yao, H., Ma, W.Y.: Mining city landmarks from blogs by graph modeling. In: Proceedings of the 17th ACM international conference on Multimedia, pp. 105–114. ACM (2009)
Okuyama, K., Yanai, K.: A travel planning system based on travel trajectories extracted from a large number of geotagged photos on the web. In: Jin, J.S., Xu, C., Xu, M. (eds.) The Era of Interactive Media, pp. 657–670. Springer, New York (2013). https://doi.org/10.1007/978-1-4614-3501-3_54
Ye, M., Yin, P., Lee, W.C., Lee, D.L.: Exploiting geographical influence for collaborative point-of-interest recommendation. In: Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 325–334. ACM (2011)
Yuan, Q., Cong, G., Ma, Z., Sun, A., Thalmann, N.M.: Time-aware point-of-interest recommendation. In: Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 363–372. ACM (2013)
Zhang, J.D., Chow, C.Y.: GeoSoCa: exploiting geographical, social and categorical correlations for point-of-interest recommendations. In: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 443–452. ACM (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Toyoshima, M., Hirota, M., Kato, D., Araki, T., Ishikawa, H. (2018). Where Is the Memorable Travel Destinations?. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11186. Springer, Cham. https://doi.org/10.1007/978-3-030-01159-8_28
Download citation
DOI: https://doi.org/10.1007/978-3-030-01159-8_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01158-1
Online ISBN: 978-3-030-01159-8
eBook Packages: Computer ScienceComputer Science (R0)