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【Purpose /significance】From the perspective of patent technology composition and association, reveal the compo⁃
sition structure, structural relationship and their changes of patented technologies in the industrial field.【Method /process】
Construct a research framework based on social network analysis methods and technology life cycle theory. Taking the field
of artificial intelligence as an example and the Derwent patent database as the data source, extract the IPC sub-category re⁃
lated information that characterizes the patented technology in the obtained patent data, and construct the patent technology
composition and correlation analysis indicators in the industrial field. Combining the technology life cycle in the field of ar⁃
tificial intelligence, analyzes the evolution of patented technologies in the field of artificial intelligence from the perspec⁃
tives of the technical composition, technical relevance, and technological change of patented technologies in the industrial
field.【Result / conclusion】Patented technologies in the field of artificial intelligence continue to break through and reorga⁃
nize to form a patented technology composition structure that covers a wider range of patented technologies, is more closely
related, and has a more stable structure; Applied patented technology in the field of artificial intelligence has become more
and more prominent in the structural relationship over time, but Basic patented technology is still the core of the structural
relationship; the core patented technology in the field of artificial intelligence at this stage is a well-developed patented
technology in the early stage. The change of patented technology at each stage of the technology life cycle has little impact
on the composition and structural relationship of patented technology. 相似文献
2.
【Purpose /significance】From the perspective of core patents identification and evolution, this paper analyzes
core technology and its changes in the industrial field.【Method /process】From the perspective of behavioral effects and
purpose, the core patents identification index system is constructed. Based on entropy-weighted method and grey correla⁃
tion analysis method, screen core patents, then analyze the evolution of technologies and owners in combination with tech⁃
nology life cycle. Conduct an empirical study with the patent data in the field of artificial intelligence.【Result / conclusion】
Three indicators of behavioral effects perspective have a great impact on identifying core patents. 201 core patents of which
the technical scope is expanding are screened. Technologies such as electrical computers and digital data processing sys⁃
tems, voice recognition, digital information transmission, and telephone or wireless communication should attract attention.
Apple, Phoenix Solutions, Cognex, Siebel Systems and Microsoft have many core patents. 相似文献
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