Mobile Learning Requirement Mining for Mobile Phone Based on Multi-Objective Evolutionary Algorithm
Most community discovery methods conduct the best community determination based on network topology and edge density,but these methods have a very high computational complexity and they are definitely sensitive to the form and type of the network.To solve these problems,an interactive optimization algorithm for weibo community based on the adaptive incremental model of dynamic nodes was proposed in this paper.Based on the optimization of the interaction between members in each community,this algorithm adopted the greedy algorithm to effectively search for the candidate of the optimal community without a traversal of all nodes.The model could quickly and accurately measure the interaction difference between inter-communities and intra-communities.Finally,the simulation test on data capture on the benchmark test network and Sohu Weibo platform showed that the proposed algorithm was superior to the selected comparison algorithm in terms of recall rate,accuracy rate,algorithm calculation time and network coverage rate.
Mobile social interaction Community discovery Multi-objective learning Self-adaptation
Zhang Ting
Information Technology Center,Beijing Jiaotong University,Beijing,100044,China
国际会议
大连
英文
303-307
2018-12-21（万方平台首次上网日期，不代表论文的发表时间）