• Dr. P.R. Devale
• Pradnya Kapadnis

On web big data are increases in both industrial and research area such as health care, financial services and commercial recommendation. The personalized travel recommendation work on user’s personal requirements, community-contributed photos and heterogeneous metadata related this photo. The existing system cannot work on the user’s requirements and cannot automatically mine user travel interest. The personalized travel sequence map both users and routes textual descriptions to the topical package space to get user topical package model and route topical package model. We used the Facebook data to find out the user’s point of interests. The POI of user is mined through Facebook data of user by Levenshtein distance algorithm.

Check-in, geo-tagged photos, GPS, social media, multimedia information retrieval, Online interest, Travel recommendation

"Personalized Travel Recommendation based on Facebook data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.57-60, May-2019, Available :http://www.jetir.org/papers/JETIR1905M11.pdf

"Personalized Travel Recommendation based on Facebook data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp57-60, May-2019, Available at : http://www.jetir.org/papers/JETIR1905M11.pdf