One of the major challenges when licensing, transacting, or managing SEPs is that there is no public database that provides information about verified Standard Essential Patents (SEPs). Standard-setting organizations (SSOs) such as ETSI (4G / 5G), IEEE (Wi-Fi), or ITUT (HEVC/VVC) maintain databases of so-called self-declared patents to document the fair, reasonable and non-discriminatory (FRAND) obligation. However, SSOs do not determine whether any of the declared patents are essential, nor are the declarants required to provide any proof or updates.

To summarize: There are two big problems. Not all declared patents are essential and not all essential patents are declared. Both described scenarios show that patent declaration data needs refinement, filtering, extrapolation and a neutral and objective SEP determination and valuation metric. In the past, SEP essentiality determination was solely conducted by subject matter experts (SMEs) who mapped and charted patent claims and standards sections. However, there is no practical way for humans to determine patent essentiality for large populations of declared patents. Not only are there too many patents (IPlytics counts over 300,000 world-wide declared patents) but it is rare for e.g. two different experts to agree on the other’s approach to mapping patents to standardized technologies as any claim chart is biased towards the company commissioning the claim charting work.

This report provides insights about how AI-based semantic claim section comparisons and cross correlation of inventor participation and the submission of accepted technical contribution at standards meetings are strong indicators of patents being relevant to a given standard and can be integrated as features in AI-based SEP prediction models that score patents as to their likelihood of being standard essential. While AI-based SEP determination may not replace the work of experts, it supports valuating and determining essentiality of SEPs for various use cases:

  • Patent portfolio manager use AI-based SEP determination to valuate their own portfolio in comparison to competitor portfolios with regards to essential assets.
  • Patent licensing manager use AI-based SEP determination to understand the value and relevance of a licensed patent portfolio with regards to standards.
  • Patent transaction manger use AI-based SEP determination to identify and valuate SEP portfolios for patent acquisition purposes – to understand what can likely commercialized and what rather not.
  • Economists use AI-based SEP determination to valuate a potential SEP portfolio share in course of a top-down analysis – to calculate the numerator and denominator.

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