Combining natural language processing techniques and algorithms LSA, word2vec and WMD for technological forecasting and similarity analysis in patent documents-Reference-Cited by-同舟云学术

Combining natural language processing techniques and algorithms LSA, word2vec and WMD for technological forecasting and similarity analysis in patent documents

Published:2022-08-09 Issue: Volume: Page:1-22
ISSN:0953-7325
Container-title:Technology Analysis & Strategic Management
language:en
Short-container-title:Technology Analysis & Strategic Management

Author:

Rezende João Marcos de¹,Rodrigues Izabella Martins da Costa¹^ORCID,Resendo Leandro Colombi¹^ORCID,Komati Karin Satie¹^ORCID

Affiliation:

1. Graduate Program in Applied Computing (PPComp), Federal Institute of Espírito Santo (IFES), Serra, Brazil

Funder

FAPES

CAPES

CNPq

Publisher

Informa UK Limited

Subject

Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/09537325.2022.2110054

Reference33 articles.

1. Allahyari, M., S. Pouriyeh, M. Assefi, S. Safaei, E. D. Trippe, J. B. Gutierrez, and K. Kochut. 2017. A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques. arXiv preprint arXiv:1707.02919.

2. Forecasting technology success based on patent data

3. The state-of-the-art on Intellectual Property Analytics (IPA): A literature review on artificial intelligence, machine learning and deep learning methods for analysing intellectual property (IP) data

4. Text matching to measure patent similarity

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