摘要
随着大数据和智能时代的到来,机器学习的研究重心已开始从感知领域转移到认知计算(Cognitive computing,CC)领域,如何提升对大规模数据的认知能力已成为智能科学与技术的一大研究热点,最近的深度学习有望开启大数据认知计算领域的研究新热潮.本文总结了近年来大数据环境下基于深度学习的认知计算研究进展,分别从深度学习数据表示、认知模型、深度学习并行计算及其应用等方面进行了前沿概况、比较和分析,对面向大数据的深度学习认知计算的挑战和发展趋势进行了总结、思考与展望.
With the advent of the era of big data and artificial intelligence, the research focus of machine learning has shifted from perception domain to cognitive computing （CC） domain. How to improve the cognitive ability through big data is becoming a research hotspot of intelligence science and technology, in which recent deep learning has been expected to spark a new wave of research on cognitive computing. This paper summarizes the research progress of cognitive computing based on deep learning in recent years. And, comparison and analysis of recent progress in deep learning and cognitive computing are presented from three aspects, that is, deep learning data representation, cognitive models, parallel computing and its applications in the big data environment. Finally, some challenges and development trends of cognitive computing based on deep learning for big data are investigated to for cast the future research.
出处
《自动化学报》
EI
CSCD
北大核心
2017年第11期1886-1897,共12页
Acta Automatica Sinica
基金
国家自然科学基金(61672217
61370097)资助~~
关键词
深度学习
认知计算
张量数据表示
并行计算
大数据
Deep learning （DL）, cognitive computing （CC）, tensor data representation, parallel computing, big data
