Measuring similarity between patents is an essential step to ensure novelty
of innovation. However, a large number of methods of measuring the similarity
between patents still rely on manual classification of patents by experts.
Another body of research has proposed automated methods; nevertheless, most of
it solely focuses on the semantic similarity of patents. In order to tackle
these limitations, we propose a hybrid method for automatically measuring the
similarity between patents, considering both semantic and technological
similarities. We measure the semantic similarity based on patent texts using
BERT, calculate the technological similarity with IPC codes using Jaccard
similarity, and perform hybridization by assigning weights to the two
similarity methods. Our evaluation result demonstrates that the proposed method
outperforms the baseline that considers the semantic similarity only.

提出了一种混合方法来自动测量专利之间的相似度，该方法考虑了语义和技术上的相似性，并使用 BERT 评估文本之间的语义相似度，使用 Jaccard 相似度计算 IPC 代码之间的技术相似度，并通过为两个相似度方法分配权重进行混合化。评估结果表明，该方法优于仅考虑语义相似性的基线。