The Construction of Demand-Driven Cross-Disciplinary Patent Technology Mining Method
In the current paradigm of open innovation,swiftly and accurately identifying external knowledge resources and exploring innovation opportunities become imperative.Patents,as a crucial source of intelligence,represent one of the most significant outcomes of technological research and the most effective carrier of technical information.The essence of patent mining lies in uncovering potential implicit information within patents through various processing techniques such as manipulation,combination,and statistical analysis,ultimately transforming it into intelligence and knowledge serving innovation endeavors.In the realm of product design,demands reflect users'requirements and expectations,constituting the starting and ending points of product design.Excitement-based demands often serve as the objects of exploration for enterprises and the direction for product evolution.Many product innovations,especially breakthrough innovations,fundamentally involve the transfer of cross-disciplinary technological characteristics.However,efficiently and accurately uncovering patent technologies relevant to enterprise products from a vast pool of patent information remains a pertinent challenge.This paper establishes a patent retrieval model through demand-function mapping and function generalization,with an extension based on IPC classification to ensure the comprehensive extraction of patent mining data.It further screens and evaluates patents through multiple dimensions,employs natural language processing technology to assist in extracting technical information,uncovers opportunities for cross-disciplinary technological feature transfer and early-stage solutions,and finally evaluates the early-stage solutions based on the laws of technological system evolution.From this,the paper proposes a demand-driven approach for cross-disciplinary patent technology mining.It utilizes natural language processing technology to extract and analyze patent data,facilitating cross-disciplinary patent technology mining to generate early-stage solutions and creatively evaluate them based on the theory of technological system evolution.Moreover,a case study on cooker hoods demonstrates the high accuracy and efficiency of this method in cross-disciplinary patent technology mining.Besides,most of the patent mining work is completed by computer,which is proved to save manpower,as well as improve the efficiency.
patent miningdemand-drivingpatent informationtechnology feature transferinformation extractiontechnology system evolution theoryproduct innovation
NETL
NSTL
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