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

当前位置： X-MOL 学术 › Math. Probl. Eng. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

An Algorithm Combining Latent Dirichlet Allocation and Bimodal Network for Evaluating Goal Deviation of Intellectual Property Strategy Execution in China
Mathematical Problems in Engineering Pub Date : 2020-11-21 , DOI: 10.1155/2020/6644465
Bing Sun ₁ , Mingxing Yu ₁ , Zaoli Yang ₂

Affiliation

China has implemented the intellectual property strategy since 2008 to support innovation-driven development. However, statistical data issued during the “12th Five-Year Plan” (2011–2015) showed that there are certain deviations between the actual and expected intellectual property strategy’s goals. To effectively diagnose the goal deviation, an algorithm combining the latent Dirichlet allocation and bimodal network based on policy text was proposed. In this method, topics in intellectual property policy texts of China’s provincial regions were extracted through the latent Dirichlet allocation model, and a bimodal network centered at provincial administration district-policy topics was constructed. Subsequently, the characteristics of the goal execution deviation of the IPS in the provincial government were explored based on the centrality of the bimodal network and singular value decomposition. Finally, some diagnosis results and conclusions were demonstrated to provide reasonable methods for evaluation of national strategic planning and promoting policy performance.

更新日期：2020-11-22

点击分享查看原文

点击收藏

公开下载

阅读更多本刊最新论文本刊介绍/投稿指南11