Temporary mobile social networks has been used at hotels, concerts, theme parks, and sports arenas, where people form a mobile social group for a short time with a common interest or activity. People confined to such specific places or activities are allowed to join the temporary mobile social networks using their main social network accounts (e.g., Foursquare, Facebook). Users registered for the same business/research conference may have common connections and thus may be willing to travel together in the conference city. Traveling with temporal friends can improve the mobile users' experiences as well as help them save money. Currently, renting cars to travel around becomes very general, and one car usually can contain at least four guests. Therefore, traveling with temporal friends can help those guests save their travel cost, such as renting cost and oil cost. To this end, in this paper, we propose a group-wise itinerary planning framework to improve the mobile users' experiences. The experiment results over real data sets illustrate the effectiveness of our proposed framework. INDEX TERMS Travel planning, temporal mobile social network, mobile computing.
Temporary social network has been a increasing popular field in the last few years where people form a temporary social group for a short time period with common interests or purposes in the same area. When a user attends an event or conference in a new city, he/she can join the temporary social networks with his/her social account. Users who attend the same academic conference or activity may have similar interests and time schedules, so they are willing to travel together. Recently, renting cars to travel has become very common, since it helps improve user experience as well as save travel costs (e.g., renting and oil costs). Thus, we propose a group-wise itinerary planning framework to minimize the travel costs for each user in a temporary social network. Experimental results conducted on real-world data sets confirm the efficiency and effectiveness of our proposed framework.
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