Abstract
As companies aim to enhance and expand their product portfolios, Technology Opportunity Discovery (TOD) has gained increasing interest. To comprehend the role of emerging technologies in innovation, we introduce a novel technology-market corpus in English and Japanese languages, and conduct a comprehensive empirical evaluation of the linkage between technology and the market. Our dataset comprises English patents extracted from the USPTO database and Japanese patents from the Japanese Patent Office (JPO), along with their associated products for each stock market company. We compare several static and contextualized word embedding methods to construct a technology-market space and propose an effective methodology based on a fine-tuned BERT model for linking technology to the market.- Anthology ID:
- 2024.lrec-main.663
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 7510–7520
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.663
- DOI:
- Cite (ACL):
- Amir Hazem, Kazuyuki Motohashi, and Chen Zhu. 2024. From Technology to Market. Bilingual Corpus on the Evaluation of Technology Opportunity Discovery. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 7510–7520, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- From Technology to Market. Bilingual Corpus on the Evaluation of Technology Opportunity Discovery (Hazem et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2024.lrec-main.663.pdf