A Study Of The Community Search Problem On Uncertain Spatial Graphs

With the rapid development of social informatization,the role of social networks in people's daily life has become increasingly prominent,and social networks have developed rapidly in both types and scales.Therefore,the research on social networks is very important in society.Value and practical significance.There are a variety of treasure research issues in social networks,such as community search,geographic location information,edge uncertainty,and so on.Community search is to unearth a researchworthy target community structure from a large social network,and the existence of the location information of the node makes the community more meaningful,and the uncertainty of the edge makes the community more in line with actual needs.Aiming at existing social networks that only contain nodes and edges connecting nodes and nodes,this paper adds the geographic location information of nodes and the uncertainty of edges to such social networks and proposes the concept of uncertain spatial networks.And conducted a research on the community search problem on the uncertain space network.In order to better study the community search problem in the uncertain space network,this paper proposes the concept of K-R-? community.In order to solve the problem of K-R-? community search in the uncertain space network.This paper first proposes a linear search method,that is,the product of the two different data of the geographic location information of the node in the space and the uncertainty of the edge is performed,and the community search problem is further carried out according to the result of the calculation.Research,according to this idea,this paper proposes the LCS algorithm.In order to make the algorithm more efficient and accurate in terms of efficiency and accuracy,this paper proposes an optimized algorithm based on the LCS algorithm,the LCSN algorithm.Although the linear search method can effectively solve the problem of K-R-?community search in the uncertain space graph,but for the two different parameters of the spatial position information and the uncertainty of the edge,sometimes,we will Faced with the problem of wanting to select a closer distance and the weight is within a certain acceptable range,or the larger weight and the distance is within the acceptable range.This paper proposes a two-dimensional-based solution to such a demand,namely the 2d CS algorithm.The basic idea of the 2d CS algorithm is to take the spatial position information of the nodes and the uncertainty of the edges as the abscissa and ordinate of the twodimensional coordinate axis respectively,and then screen nodes according to the size of the abscissa and ordinate to obtain the K-R-? community.Based on the 2d CS algorithm,the optimization algorithm 2d CSN algorithm is proposed,so as to solve the problem of K-R-? community search in the uncertain space network according to the importance of different information.Through a mass of experiments on several real data sets,the effectiveness and accuracy of the proposed algorithms for community search on uncertain spatial networks are proved.