商标
专利分析
知识流
质量(理念)
技术预测
人工智能
计算机科学
技术变革
引用
订单(交换)
技术开发
欧洲专利局
业务
知识管理
数据科学
工程类
国际贸易
财务
万维网
哲学
制造工程
操作系统
认识论
作者
Chun‐Yao Tseng,Ping-Ho Ting
标识
DOI:10.5172/impp.2013.15.4.463
摘要
AbstractArtificial intelligence (AI) plays a key role in knowledge economies, because it can be used to develop systems that think like humans, act like humans, think rationally, and act rationally (Russell & Norvig, 2010). In this study, we divide AI into four sub-technological fields: Problem reasoning and solving, machine learning, network structures, and knowledge processing systems. This study investigates three main issues related to the technology development of AI. First, the aggregate technology development of AI is examined, and the four sub-technological fields of AI are compared. Second, we employ measures of patent quantity and patent quality to demonstrate the technology development of AI in different countries. Finally, we investigate the technology positions of different countries in the four sub-technological fields of AI. By analyzing a patent and citation dataset comprised of all patents granted by the United States patent and trademark office from 1976 to 2010, we obtain empirical findings that help us understand the technology development of AI in different countries. The major contributions of this study are four measures of patent quantity (PCA, PCI, SHAI, and SHIA) and three measures of patent quality (citation ratios, CII, and TCT). These measures are helpful in understanding technological development of AI in different counties. Moreover, we use patent citation data and investigate the technology flow in AI, in order to determine the technology position of different countries in the four sub-technological fields of AI.Keywords: artificial intelligencetechnology developmentpatent and citation analysistechnology flow
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