First. we use graph theory to further clarify information of nodes and topics. Next, our paper analyzes the factor which affects the nodes probability of being conspirators. According to requirement 1, each node is gi...First. we use graph theory to further clarify information of nodes and topics. Next, our paper analyzes the factor which affects the nodes probability of being conspirators. According to requirement 1, each node is given an initial probability in being a conspirator on the basis of the acquired information.Then we conduct calculations with the iterative equation produced by factor analysis to get the priority list of the 83 given nodes. In addition, according to requirement 2, we make some changes of the nodes information before solving the iterativc modcl above. Compared with former result, some changes of priority and probability of being conspirator emerges.Finally, based upon requirement 3, we pick out some infomaation from some certain topic by semantic analysis and text analysis. A new group of indexes are solved out with TOPSIS to finish the information-gathering period. The terminal indicator, containing the information of nodes and topics, is a weighted average value of the indexes obtained above and the indexes obtained in requirement 1 with the method of the variation coefficient.展开更多
文摘First. we use graph theory to further clarify information of nodes and topics. Next, our paper analyzes the factor which affects the nodes probability of being conspirators. According to requirement 1, each node is given an initial probability in being a conspirator on the basis of the acquired information.Then we conduct calculations with the iterative equation produced by factor analysis to get the priority list of the 83 given nodes. In addition, according to requirement 2, we make some changes of the nodes information before solving the iterativc modcl above. Compared with former result, some changes of priority and probability of being conspirator emerges.Finally, based upon requirement 3, we pick out some infomaation from some certain topic by semantic analysis and text analysis. A new group of indexes are solved out with TOPSIS to finish the information-gathering period. The terminal indicator, containing the information of nodes and topics, is a weighted average value of the indexes obtained above and the indexes obtained in requirement 1 with the method of the variation coefficient.