%A Fu Zhu, Ding Weike, Guan Peng, Ding Xuhui %T Knowledge Description Framework for Foreign Patent Documents Based on Knowledge Meta %0 Journal Article %D 2022 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2021.0921 %P 263-273 %V 6 %N 2/3 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_5308.shtml} %8 2022-03-25 %X

[Objective] This paper proposes a new knowledge description framework (KDF) for foreign patent documents based on knowledge meta, aiming to generate better full-text features of these documents from the fine-grained perspective. [Methods] First, we analyzed the U.S. and European patents to compare their differences to Chinese documents. Then, we used knowledge meta to describe the full-text features of foreign patents with external and content features to construct the KDF. Finally, we analyzed the semantic relationships of the contents from this new framework. [Results] The KDF generated eight core knowledge elements and their description rules, which had four types of semantic relationships between patent documents and knowledge elements, as well as five types of relationships between different knowledge elements. [Limitations] The adaptability of the KDF needs to be strengthened. [Conclusions] The proposed KDF could describe the full-text knowledge features of foreign patent documents effectively and reveal the semantic relationship between the knowledge features, which provides new directions for knowledge organization, mining and services of patent documents.