Natural Language Processing Patents Landscape Analysis

Hend S. Al-Khalifa (), Taif AlOmar and Ghala AlOlyyan
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Hend S. Al-Khalifa: Department of Information Technology, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh 11543, Saudi Arabia
Taif AlOmar: iWAN Research Group, King Saud University, Riyadh 11543, Saudi Arabia
Ghala AlOlyyan: iWAN Research Group, King Saud University, Riyadh 11543, Saudi Arabia

Data, 2024, vol. 9, issue 4, 1-17

Abstract: Understanding NLP patents provides valuable insights into innovation trends and competitive dynamics in artificial intelligence. This study uses the Lens patent database to investigate the landscape of NLP patents. The overall patent output in the NLP field on a global scale has exhibited a rapid growth over the past decade, indicating rising research and commercial interests in applying NLP techniques. By analyzing patent assignees, technology categories, and geographic distribution, we identify leading innovators as well as research hotspots in applying NLP. The patent landscape reflects intensifying competition between technology giants and research institutions. This research aims to synthesize key patterns and developments in NLP innovation revealed through patent data analysis, highlighting implications for firms and policymakers. A detailed understanding of NLP patenting activity can inform intellectual property strategy and technology investment decisions in this burgeoning AI domain.

Keywords: NLP; patents; innovation; artificial intelligence; lens patent database (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2024
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