Research Article

An Algorithm Combining Latent Dirichlet Allocation and Bimodal Network for Evaluating Goal Deviation of Intellectual Property Strategy Execution in China

Table 5

SVD data of nodes in provinces.

ProvinceFactor 1Factor 2Factor 3

Beijing0.338−0.3020.078
Tianjin0.204−0.068−0.053
Hebei0.085−0.045−0.001
Shanxi0.0860.0810.029
Nei Mongol0.073−0.1070.115
Heilongjiang0.207−0.352−0.071
Jinlin0.126−0.244−0.047
Liaoning0.261−0.1510.167
Shanghai0.353−0.286−0.129
Jiangsu0.245−0.1380.116
Chongqing0.150.036−0.154
Sichuan0.2460.334−0.227
Yunnan0.2360.014−0.223
Shaanxi0.0620.078−0.153
Gansu0.2340.121−0.184
Qinghai0.1910.467−0.208
Ningxia0.0650.1170.217
Xinjiang0.0910.039−0.345
Hainan0.026−0.005−0.118
Guizhou0.0220.0070.089
Zhejiang0.07−0.061−0.049
Anhui0.167−0.0420.25
Fujian0.1560.086−0.068
Jiangxi0.1670.2020.337
Shandong0.092−0.057−0.038
Henan0.119−0.0170.142
Hubei0.1160.0710.269
Hunan0.2420.131−0.068
Guangdong0.2120.220.013
Guangxi0.2040.2870.466