TCMA:Improved L-shell Local Community Mining Algorithm And Experimental Study

In recent years,everyone can see that human has made remarkable achievements in the field of science and technology,especially in the field of Internet.The rapid development of network technology,especially in the mobile Internet development has made a qualitative change in people's work and lifestyle.Since the advent of the mobile Internet,people have been dependent on the Internet in all aspects,such as people's life and work.This fully illustrates that the Internet has been linked to our lives closely,forming an indivisible whole.As we all know,in the Web2.0 network period,the most prominent development is the advent of the social networking services and the great changes to people's lives and work.After that,regardless of any person,age,industry,and nationality,everyone can access and release the message fairly and faston the Internet.This sudden way of life makes people feel that Zhuge Liang is alive.Every netizen gets the ability and thinking ways that "No one knows theworldwithout a cub".Especially in the social network generated social software,such as Sina microblogging,Tencent QQ and We Chat and foreign social software Twitter and so on a variety of social software,making every corner of the world's Internet users are closely connected Together.We can see the network as a network that can cover the world,in this huge network,each of our network users can be regarded as a node of the network.We communicate with each other through network tools and other operations.Now that it has grown to large data,the number of Internets in the era of large data is more complex and bulky,and the amount of data in the big data age is more than ever,and it can be said to be more than the sum of all the previous data.In the era of large,data network data is so large,mainly due to the rapid development of network science and technology.These massive amounts of data can not only reflect the circle of life,summed up the past,but also speculate andpredictwhat will happenon the futurethrough these massive data.That makes the study of the Internet more practical significance and the use of the value.In this paper,the algorithm of the existing community network is deeply researched and analyzed,and the L-shell algorithm based on the local community mining algorithm is improved.In the process of finding the nodes that to be excavatedin the community,Trust relationship judgment is added.This idea can greatly enhance the efficiency and accuracy of the community discovery algorithm.In addition,the algorithm of this paper is a kind of targeted community mining algorithm design,mainly for the trust relationship model of the network model for community mining.The purpose of this design is to dig outthe community through the trust relationship.The community within the nodes have a certain degree of similarity.So more practical value and significance can be targeted information push and other activities.Although there are a lot of research on the community mining algorithm,it is difficult to find a social network in the community structure of the accuracy itselfin most cases,especially in the network structure of the number of nodes.When the nodes reach hundreds of thousands,Millions of time,the structure of the network will become quite complex.If the whole network from the whole network division,it is meaningless and the efficiency of the algorithm will be reduced then.And when the accuracy rate is not high,it can simply but not effectively reflect the real community situation.And if dividing the community as the local community from the perspective of mining algorithms,it is not the same.If dig out the node of the communitythrough a starting node,mining out of the community is more valuable.So in recent years,the community excavation of the local mining algorithm has been keen the point of study.The nature of the community discovery algorithm refers to a process of clustering a node,and the nodes associated with each other are joined together so that the corresponding community structure is obtained.The working arrangement of this paper mainly including the following aspects: The research and analysis of the community mining algorithm is mainly based on the L-shell algorithm in the local community mining algorithm(described below)and the R algorithm(described below)Analysis.Then the L-shell algorithm is improved accordingly.Since the algorithm isfor the community with the trust relation model network,it also makes a lot of research and analysis on the knowledge of the trust relationship among the nodes in the community.Then the improved L-shell algorithmrefers to the trust relationship,which based on community mining algorithm(hereinafter referred to as TCMA)for code design and implementation.Then the experimental results of TCMA algorithm are analyzed.