NLP软件专利:实证回顾

Brian Haney
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引用次数: 1

摘要

自然语言处理(NLP)专利是技术专利市场中增长最快的细分市场之一。NLP技术为最新的人工智能(AI)应用提供了动力。例如,NLP技术支持苹果的Siri、亚马逊的Alexa和Facebook的好友推荐系统。然而,虽然关于软件专利的文献正在明显扩大,但专门关注NLP专利的文献却不存在。本文借鉴了越来越多的计算语言学、知识产权和技术法律奖学金,提供了新颖的NLP专利分析和批评。此外,本文还贡献了第一个实证NLP专利审查,包括新颖的软件描述、市场建模和与专利权利要求相关的法律分析。首先,本文讨论了开发NLP软件的两种主要技术方法。其次,本文对一个不断发展的NLP专利数据集进行建模,提供经济见解、法律权利要求分析和专利估值策略。
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Patents for NLP Software: An Empirical Review
Natural language processing (NLP) patents are one of the fastest growing niche segments in the technology patent marketplace. NLP technologies power the latest in Artificial Intelligence (AI) applications. For example, NLP technology supports Apple’s Siri, Amazon’s Alexa, and Facebook’s friend recommendation system. Yet, while the literature on software patents is visibly scaling – the literature specifically focused on NLP patents is non-existent. This Article draws on a growing body of computational linguistics, intellectual property, and technology law scholarship to provide novel NLP patent analysis and critique. Further, this Article contributes the first empirical NLP patent review, including novel software descriptions, market modeling, and legal analysis relating to patent claims. First, this Article discusses the two main technical approaches to developing NLP software. Second, this Article models an evolving NLP patent dataset, offering economic insights, legal claims analysis, and patent valuation strategies.
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