Research On Business Location Selection In Geo-social Networks

Location selection is the most important one among many issues to consider when looking for a place to establish a new business,because location can mean the difference between feast or famine for many businesses.Traditionally,the business owners pick their locations mainly based on how many potential customers will pass by the place periodically.Therefore,the most ideal locations are always distributed in the popular business districts,like a big shopping mall.However,the rentals of the stores located in such places are very expensive accordingly.It would make the business owners difficult to make satisfied profits.The existing works typically utilize the number of customers who are the Reverse Nearest Neighbors(RNN)of a business location to assess its goodness.While,with the prevalence of word-of-mouth marketing in social networks,a business can now exploit the social influence to attract enormous customers to visit it,even though it is not located in the popular but unaffordable business districts.In this paper,we propose two business location selection approaches to integrate the factors of both social influence and geographical distance,and they are called as the relative distance aware business location selection and the competitive and targeted aware business location selection respectively.For the relative distance aware business location selection method,we propose a relative distance aware influence diffusion model,and the goodness of a location is assessed by the maximum number of social network users it can influence via online propagation.The competitive and targeted aware business location selection method considers the impact of absolute distance,which is ignored by the relative distance aware business location selection method,and the targeted users are considered.The competitive and targeted aware business location selection method exploits the maximum number of targeted users that a location can influence to evaluate the location's attractiveness.Moreover,two business location selection approaches propose pruning rules to speed up the selection of the optimal business location,and design different algorithms to estimate a location's attractiveness.Lastly,we conduct the experiments on real geo-social networks,and compare the proposed business location selection methods with the existing approaches to demonstrate the effectiveness and efficiency of our approaches.