Individualized Travel Recommendation by Mining People Ascribes and Travel Logs Types from Community Imparted Pictures

نویسندگان

  • S. Saranya
  • S. Sivaranjani
  • G. Surya
  • A. Ramachandran
چکیده

Leveraging community imparted data for personalized recommendation is one of the active research problems since there are rich contexts and human activities in such explosively growing data. We focus on personalized travel recommendation and show promising applications. We conduct personalized travel recommendation by considering specific user profiles or attributes. We propose a personalized travel recommendation model considering users’ attributes as well as their group types and the knowledge mined from travel logs .We investigate the association of people attributes such as time, popular landmarks, etc., We also recommend the nearby location suggestions in mobile using android. Keyword – data, travel recommendation, location suggestions.

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تاریخ انتشار 2014