Standard-essential patents (SEPs) are an important technological resource for firms in the telecommunication industry. The utilisation of technological topic analysis to reveal the global development dynamics of SEPs has significant theoretical and practical implications. First, this study defines the phrase extraction rules and constructs a phrase importance evaluation model to extract key technical phrases in the patent text. Second, the extracted key phrases are used as input for the Latent Dirichlet Allocation (LDA) model, and the relative independence (RI) model is proposed to determine the optimal number of topics based on two dimensions of coherence and similarity. Finally, the technological topic analysis based on the improved LDA model is performed on 30,154 texts of declared 5G SEPs. The results show that (1) the RI model can better identify the optimal number of topics for the LDA model; (2) 23 key technologies and four hot spots in 5G are identified based on the improved LDA model; (3) different firms have different technological layouts, and the diversification trend of technology development appears; and (4) the forecasting results also reveal the dynamics of emerging and declining technical areas in the 5G industry.

: Employing Landsat data, quantitative indicators relating to urban spatial structure in China—including an urban compactness ratio and an urban elongation ratio—from 2007 to 2016 were selected and quantified. The panel data model indicated that urban compactness was negatively correlated with the urban GDP. Urban elongation was positively correlated with the urban GDP. But the urban elongation and the consumption of land resources cannot sustain urban economic growth in the long run. Therefore, to give full play to the economic benefits of spatial agglomeration and to curb the extensive elongation of urban spatial structure, there is an urgent need to reform the current urbanization mode and employ a market mechanism, changing the single government-regulated mode into a multi-subject cooperative mode.

This article comprehensively investigates the differences between standard-essential patents (SEPs) and nonstandard-essential patents (N-SEPs) in terms of knowledge sources, novelty, and generality and investigates the impact of knowledge sources on novelty and generality. Specifically, we take a sample of declared SEPs related to long-term evolution standards and their corresponding N-SEPs from 2006 to 2015. To explore the differences between SEPs and N-SEPs in terms of knowledge sources, we used patent bibliometric analysis and text analysis methods to mine the technological domain, scientific literature, and standard literature involved in the backward citations of patents. Then, three indicators are established: 1) technological diversity, 2) science linkage, and 3) standard linkage. Standard linkage has rarely been discussed in the literature. We used text analysis to construct two indicators, the novelty and generality indices, which depict the differences in novelty and generality between SEPs and N-SEPs by comparing the text similarity of focal patents to prior and subsequent patents. The impact of different knowledge sources on SEPs and N-SEPs was verified through empirical analysis. This article innovatively found that SEPs are less technologically diverse and scientifically related, whereas their standard linkage is higher than that of N-SEPs. SEPs are more generic and less novel than N-SEPs. In addition, different knowledge sources have distinct effects on the novelty and generality of SEPs and N-SEPs. These findings can provide a reference for firms’ knowledge acquisition, resource allocation, and selection of R&D partners in the patent creation process.