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AI patent screening framework uses citation dynamics to identify disruptive candidates

Researchers have developed a machine-learning framework that uses a "CD index" derived from citation network dynamics to identify and prioritize potentially disruptive patent candidates in artificial intelligence. This interpretable framework aims to screen patents ex ante, offering a new method for evaluating innovation in the AI field. AI

IMPACT Provides a novel method for evaluating and predicting the impact of AI-related patents.

RANK_REASON The cluster describes a research paper detailing a new framework for patent analysis. [lever_c_demoted from research: ic=1 ai=1.0]

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AI patent screening framework uses citation dynamics to identify disruptive candidates

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  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    "A CD index guided ensemble framework for screening potentially disruptive patent candidates in artificial intelligence" Building on the CD disruptiveness measu

    "A CD index guided ensemble framework for screening potentially disruptive patent candidates in artificial intelligence" Building on the CD disruptiveness measure derived from citation-network dynamics, this study develops an interpretable machine-learning framework to screen and…