GPS Estimation for Places of Interest From Social Users' Uploaded Photos

Travel Guide- A Personalization Of Travel Package Recommendation System

“…Personalization is one of system that will give user various type of information access of other user personalization is based on user point of interest in [1]. using the GPS trajectories generated by multiple users.…”

“…they consider an individual"s visit to a location as a link from the individual to the location, and map this links in terms of the users travel experiences in various regions. [1] this method mines the shared check-in patterns for users from different regions and then utilizes the shared patterns to further explore more similar user across regions. user can transfer knowledge across regions to recommend for an user in a new region [2] The new solution is simple and fast the given solution improves accuracy from 48% for a traditional BOW solution to 60%, while maintaining the same processing time [3] Our experimental results demonstrate the significance it would be interesting to investigate the recommendation effect of content information compared to other information, such as spatial, temporal, or social information [4] they focus on the problem of time-aware POI recommendation, which considers the temporal influence in user activities they for POI recommendation on the GTAG.…”

A Survey of Geo-tagged Multimedia Content Analysis within Flickr

“…certain words may be associated with certain countries. Finally, Li et al [69] removed "noisy" photos, i.e. photos that cannot contribute sufficiently to location estimation.…”

Travel Recommendation Based on Data From Social Media

“…Big media, especially the flourish of social media (e.g., Facebook, Flick, Twitter etc.) offers great opportunities to address several difficult issues, for instance, GPS estimation [1], [2] and travel recommendation [3]. Travelogue websites (e.g., www.igougo.com) offer wealthy descriptions regarding landmarks and traveling expertise written by users.…”

“…For example, it may still not be a decent recommendation if all the POIs suggested for in the future ar in four corners of the town, even though the user is also curious about all the individual POIs. Existing studies on travel recommendation mining famous travel POIs and routes ar in the main from four sorts of huge social media, GPS trajectory [5], check-in information [4], [6], [7] geo-tags [2], [3], [8], [9], [10] and blogs (travelogues). However, general travel route planning cannot well meet users" personal necessities.…”