Identification of Probable Standard Essential Patents (SEPs) Based on Semantic Analysis of Patent Claims

Abstract

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.