In recent years, million geo-tagged photos are available in online web service like Flickr, panoramio, etc. People contributing geo-tagged photo and share their travel experiences these media. The photo itself has important information sharing reveals like location, time, tags, title, and weather. We recommend the new method locations travel for tourists according their time and their preference. We get travel user preference according his/her past time in one city and recommendation another city. We examine our technique collect dataset from Flickr publically available and taken different cities of china. Experiment results show that our travel recommendation method according to tourist time capable to predict tourist location recommendation famous places or new places more precise and give better recommendation compare to state of art landmarks recommendation method and personalized travel method.
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