Travel Location Sequence Recommendation From User’s Point of Interest
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2018-05-19 https://doi.org/10.14419/ijet.v7i2.12484 -
Location, Page Rank Algorithm, Point of Interest, Recommendation, User Feedback. -
Abstract
The major objective of any Travel Recommendation System is to recommend its users to visit the most suitable place in according to the selected location. We present this system of travel recommendation from the experiences of the previously visited users of that location. Apart from the existing systems, our approach not only limited to users traveling interest but also recommends a travel sequence. Our sys-tem also suggest best visiting time, most suitable season, preference of visiting the nearby places and traveling route to reach to your desired location. Here the user can create his friend list and can share his experience of visit to his friends. This user given experience is taken as a feedback by the system to update his recommendations.
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References
[1] V. W. Zheng, Y. Zheng, X. Xie, and Q. Yang, “Collaborative location and activity recommendations with GPS history data,†in Proc. 19th Int. Conf. World Wide Web , 2010, pp. 1029–1038. https://doi.org/10.1145/1772690.1772795.
[2] H. Yin, C. Wang, N. Yu, and L. Zhang, “Trip mining and recommendation from geo-tagged photos,†in Proc. IEEE Int. Conf. Multimedia Expo Workshops, 2012, pp. 540–545.
[3] Akshitha Sivakumar and B Prabadevi, “Tour Recommendation Guide- Personalized travel sequence recommendation†in IOP Conference Series: Material Science and Engineering, vol. 263, Computation and Information Technology, 2017.
[4] Zahra Farzanyar and Nick Cercone, “Trip Pattern Mining Using Large Scale Geo-tagged Photos†in International Conference on Computer and Information Science and Technology, Paper no. 113, May 12, 2015.
[5] Y. Gao, J. Tang, R. Hong, Q. Dai, T. Chua, and R. Jain, “W2go: A travel guidance system by automatic landmark ranking,†in Proc. Int. Conf. Multimedia, 2010, pp. 123–132. https://doi.org/10.1145/1873951.1873970.
[6] T. Kurashima, T. Tezuka, and K. Tanaka, “Mining and visualizing local experiences from blog entries,†in Database and Expert Systems Applications. New York, NY, USA: Springer, 2006, pp. 213–222.
[7] H. Huang and G. Gartner, “Using trajectories for collaborative filtering–based POI recommendation,†Int. J. Data Mining, Modelling Manage., vol. 6, no. 4, pp. 333–346, 2014.
[8] C. Zhang and K. Wang, “POI recommendation through crossregion collaborative filtering,†Knowl. Inform. Syst., vol. 46, no. 2, pp. 369–387, 2016. https://doi.org/10.1007/s10115-015-0825-8.
[9] P. Lou, G. Zhao, X. Qian, H. Wang, and X. Hou, “Schedule a rich sentimental travel via sentimental POI mining and recommendation,†in Proc. 20th ACM Int. Conf. Multimedia Big Data, 2016, pp. 33–40.
[10] Zheng V., Hu D. and Yang Q. Cross-domain activity recognition. In Proc. of the 11th Intl. Conf. on Ubiquitous Computing (Orlando, USA, 2009). ACM Press: 61-70.
[11] Zheng Y., Zhang L. and Xie X. Recommending friends and locations based on individual location history. In ACM Transaction on the Web (2010).
[12] Zheng Y., Liu L., Wang L. and Xie X. Learning transportation modes from raw GPS data for geographic applications on the Web. In Proc. of the 17th Intl. Conf. on World Wide Web (Beijing, China, 2008), ACM Press: 247-256. https://doi.org/10.1145/1367497.1367532.
[13] Jie Bao, Yu Zheng, David Wilkie, and Mohamed Mokbel “Recommendations in Location-based Social Networks:A Survey, Geoinformatica, 6 February 2015.
[14] J. Li, X. Qian, Y. Y. Tang, L. Yang, and T. Mei, “GPS estimation for places of interest from social users’ uploaded photos,†IEEE Trans. Multimedia, vol. 15, no. 8, pp. 2058–2071, Dec. 2013. https://doi.org/10.1109/TMM.2013.2280127.
[15] S. Jiang, X. Qian, J. Shen, Y. Fu, and T. Mei, “Author topic model based collaborative filtering for personalized POI recommendation,†IEEE Trans. Multimedia, vol. 17, no. 6, pp. 907–918, Jun. 2015.
[16] Jiang Shuhui, Qian Xueming, Shen Jialie, Fu Yun and Mei Tao 2015, “Model- Based Collaborative Filtering for Personalized POI Recommendations†IEEE Trans. Multimedia 17 907-918.
[17] Li Jing, Qian Xueming, Tang Yuan Yan, Yang Linjun and Mei Tao 2013, “GPS Estimation for Places of Interest from Social Users' Uploaded Photos†IEEE Trans. Multimedia 15 2058-2071. https://doi.org/10.1109/TMM.2013.2280127.
[18] Farzanyar, Z., and Cercone N. (2013) "Efficient mining of frequent itemsets in social network data based on MapReduce framework." Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. ACM. https://doi.org/10.1145/2492517.2500301.
[19] Farzanyar Z, and Cercone N. (2013)"Accelerating Frequent Itemsets Mining on the Cloud: A MapReduce-Based Approach." Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on. IEEE. https://doi.org/10.1109/ICDMW.2013.106.
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How to Cite
Laddha, S., & Aote, S. (2018). Travel Location Sequence Recommendation From User’s Point of Interest. International Journal of Engineering & Technology, 7(2), 772-776. https://doi.org/10.14419/ijet.v7i2.12484Received date: 2018-05-04
Accepted date: 2018-05-14
Published date: 2018-05-19