Location-aware Top-k Spatial-temporal Events Query by Utilizing Social Network in Location-based Services
Date Issued
2009
Date
2009
Author(s)
Tsai, Shang-An
Abstract
A Location-based Service, which is abbreviated as LBS, is defined as an application that serves a user based on his/her physical locations. Various kinds of LBS are on the rise and flourishing because of the rapid development of wireless technologies, mobile devices, and position systems. Through these technologies and devices, the LBSs are developed to assist people to search, browse or interact with items physically around them. Recently, more LBSs are developed to serve mobile users, which further consider user profiles such as the user’s interest and their shopping behavior. When a group of users would like to engage in social activities together, like shopping, an LBS should consider all the user preferences in recommending a list of suitable options. However, the traditional LBSs are usually designed to serve a single user. That is, a recommendation is made to a single user based only on his profile and location. herefore, to provide LBSs for multiple users, we propose a location-aware top-k spatial-temporal event query system. Specifically, we propose a new group ranking function that considers the social relationships between the users in a group. In our design, we initially find a list of events based on the time constraints and locations of all mobile participants. Next, we grade the events according to the location and the profile of each user. Then, our algorithm ranks the candidate events based on each personal ranked list, the social network and the locations of the users. Finally, top-k events are returned. The experiment results show that the proposed system works well and receives high group satisfactions in a mobile environment when the group size is not very big, and the social impacts of people in the same group have high divergence.
Subjects
location-based services
recommendation system
social networks analysis
group decision making
mobile social network
Type
thesis
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