Synonym extraction from Japanese patent documents using term definition sentences

Conducting prior patent searches before developing technologies and filing patent applications in companies or universities is essential for understanding technological trends among competitors and academic institutions, as well as for increasing the likelihood of obtaining patent rights. In these searches, it is important not only to include relevant keywords in the search queries but also to incorporate related terms retrieved from a thesaurus. To support this, methods using word embeddings for automatically extracting such synonyms have recently been proposed. However, patent documents often contain unique expressions and compound terms, such as specialized technical terminology and abstract conceptual terms, which are difficult to accurately capture using existing large language models trained at the token level.In this study, we investigate a method for extracting synonyms from patent documents by embedding the definition sentences that explain technical terms. The experimental results demonstrate that the proposed method achieves more precise synonym extraction than conventional word embedding approaches, and it can contribute to the expansion of existing thesauri.Thus, this research is expected to improve the recall of prior art searches and support the automatic extraction of technical elements for identifying technological trends.

Authors

Publication Details

Journal
Machine Learning with Applications
Published
2026-01-21
DOI
https://doi.org/10.1016/j.mlwa.2026.100848
Primary Topic
Intellectual Property and Patents
Type
article
Field-Weighted Citation Impact
0.00
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article

Synonym extraction from Japanese patent documents using term definition sentences

Koji Marusaki, Asahi Hentona, Seiya Kawano
Machine Learning with Applications
Intellectual Property and Patents
article

Synonym extraction from Japanese patent documents using term definition sentences

Koji Marusaki, Asahi Hentona, Seiya Kawano
article en

Abstract

Conducting prior patent searches before developing technologies and filing patent applications in companies or universities is essential for understanding technological trends among competitors and academic institutions, as well as for increasing the likelihood of obtaining patent rights. In these searches, it is important not only to include relevant keywords in the search queries but also to incorporate related terms retrieved from a thesaurus. To support this, methods using word embeddings for automatically extracting such synonyms have recently been proposed. However, patent documents often contain unique expressions and compound terms, such as specialized technical terminology and abstract conceptual terms, which are difficult to accurately capture using existing large language models trained at the token level.In this study, we investigate a method for extracting synonyms from patent documents by embedding the definition sentences that explain technical terms. The experimental results demonstrate that the proposed method achieves more precise synonym extraction than conventional word embedding approaches, and it can contribute to the expansion of existing thesauri.Thus, this research is expected to improve the recall of prior art searches and support the automatic extraction of technical elements for identifying technological trends.

Machine Learning with ApplicationsVol. 23
Industry, innovation and infrastructure
Openalex Percentile: Top 84%
Intellectual Property and Patents
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Synonym extraction from Japanese patent documents using term definition sentences — Koji Marusaki, Asahi Hentona, et al. · Machine Learning with Applications (2026) | TGRS Research Map | TGRS