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User Adaptive Trip Planner

Type of publication Peer-reviewed
Publikationsform Proceedings (peer-reviewed)
Author Venkateswaran Ramya, Bereuter Pia,
Project Generalization for Portrayal in Web and Wireless Mapping (GenW 2)
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Proceedings (peer-reviewed)

Title of proceedings Ordnance Survey Geospatial Mashup Challenge
Place Durham, UK


The presented mashup application, as the name suggests, predicts and presents important places of visit to the user, depending on a number of factors, some of them being the user profile, user habits, purpose of visit to the place, accessibility, mode of transport etc. The information is divided into two parts. First is the profile or personal information, which is extracted from online social networking profiles like Facebook and travel profiles like Dopplr. This information helps in determining a pattern in tourism habits and more importantly determining what the user may want to see. Depending on the user's hobbies, interests and activities or portfolio, places of visit in the city are predicted. The second type of information that is extracted comes from selected websites on travel information and public transport information sites. Right now the place selected to work on is Paris but will be extended in the future. The goal is to point out important places for different users after looking at their profile and also after learning from places they have already been too. Other factors that affect this decision and ranking of places to visit are the purpose of travel, duration of travel, exact dates in the city, mode of transport and base address. There are other parameters like budget travel, requirement of accessibility facilities and calendar synchronization too. The information passes through a phase of being extracted from the web by an intelligent wrapper. Content is then ranked for importance depending on the different weights as discussed above, filtered for unwanted content and then formatted for the next level of presentation. The next level is the presentation, which is an "Adaptive Visualization" of the data in a personalized format. This "egocentric" view includes artificial enlargement of the important areas along with route suggestions and color coded time slots extracted from the user's private calendar, indicating free and booked time slots of the person. The time slots also suggest a duration of stay at a certain place, thus suggesting to the user an array of events with full information on routes and schedules.