基于专利权利要求语义分析的可能标准必要专利识别

Sven Wittfoth
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引用次数: 3

摘要

专利分析中最重要的任务之一是对专利进行评估,以确定其金融资产。对标准至关重要的专利,即所谓的标准必要专利(sep),是一种特别有价值的专利类型,因为对标准至关重要的专利产品和工艺主要是为大众市场设计的,通常会产生高额版税。尽管有几个委员会通过命名相关的标准代码来发布标准标准,但仍有大量的专利可能是标准标准,但尚未宣布。市场参与者对识别标准普尔,特别是潜在标准普尔很感兴趣,因为这些标准普尔可能会影响他们现在和未来的业务风险管理。除了风险问题,如果可以在自己的专利组合中确定适合作为sep的专利,还可以通过许可费获得机会。在本文中,作者提供了一种基于计算机的方法,该方法基于使用Doc2Vec算法形式的人工智能对专利权利要求进行语义分析,帮助专利持有人确定专利是否可能被宣布为SEP,以及哪些标准适合潜在的SEP。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Probable Standard Essential Patents (SEPs) Based on Semantic Analysis of Patent Claims
One of the most important tasks in patent analysis is to evaluate a patent in order to identify its financial asset. Patents that are essential for standards, so-called standard essential patents (SEPs), are an especially valuable type of patent because patented products and processes that are essential for standards are primarily designed for the mass market and often generate high royalties. Although several committees publish SEPs by naming the associated standard codes, there are a large number of patents that are likely to be SEPs but have not yet been declared. Market participants are interested in identifying SEPs, and particularly potential SEPs, as these may affect their businesses now and in the future in terms of risk management. In addition to risk issues, opportunities can also be gained through license fees if patents that are suitable as SEPs can be identified within one's own patent portfolio. In this article, the author provides a computer-based method that helps patent holders to determine whether a patent is likely to be declared an SEP and which standards are suitable for potential SEPs, based on a semantic analysis of patent claims using artificial intelligence in the form of the Doc2Vec algorithm.
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