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新加坡知识产权局:2019专利申请视角下的全球人机协作技术状况研究报告(英文版)(13页).pdf

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1、TECHNOLOGY SCAN:HUMAN&MACHINE COLLABORATION WITH INPUT FROM METHODOLOGY 1.Dataset used for the report The patent dataset was retrieved on 17 May 2019 and comprises worldwide patent applications relating to human and machine collaboration technologies published in 2009-2018.Relevant business informat

2、ion,market data,and national policies that are available from commercial databases or on the web are also used to support the findings of the report.2.Counting the number of inventions This report counts the number of inventions by the number of unique patent families.Counting individual patent appl

3、ications will result in double counting as each patent family may contain several patent publications if the applicant files the same invention for patent protection in multiple destinations.As a patent family is a group of patent applications relating to the same invention,analyses based on countin

4、g one invention per unique patent family can reflect innovation activity more accurately.3.Formulation of search strings To ensure optimal recall and accuracy of the data sets retrieved,the search strings used in this study were formulated by incorporating keywords(and their variants),as well as rel

5、evant patent classification codes and indexes,e.g.International Patent Classification(IPC)and Cooperative Patent Classification(CPC).4.Grouping of technology domains Grouping of individual patent documents into the respective technology domains was carried out based on patent classifications codes,t

6、ext-mining and semantic analysis of the patent specifications in particular claims,titles,abstracts,as well as a manual review of the individual patent applications.5.Growth rate calculation Annual growth rate refers to the average annual growth and was derived by using the best-fit exponential line

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本文主要内容为新加坡知识产权局(IPOS)发布的关于人机协作(HMC)技术趋势的报告。报告基于2009-2018年间全球范围内发表的与HMC相关的专利,对HMC技术进行了全面的趋势分析,主要关注机械、语言、情感和数字信任四个领域。报告指出,中国在HMC机械领域占据主导地位,贡献了超过60%的创新;美国在语言领域占据优势,微软、IBM和谷歌等大型跨国公司在此领域的创新尤为突出。情感领域的创新数量在2018年达到历史新高,超过3500项。数字信任领域则以可解释的AI(XAI)和AI伦理为主要创新方向。此外,报告还特别关注了机器对机器(M2M)协作和群体智能领域,指出这些领域具有强大的研发潜力。总体而言,报告认为HMC技术在商业应用方面具有巨大的市场潜力,但还需进一步研究其在各个方面的未知因素,以实现AI解决方案在关键和高风险应用中的部署。
人类与机器协作技术发展现状如何? 情感识别与机器情感合成哪个领域更具创新潜力? 数字信任领域的发展现状及未来趋势是什么?
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