计算机科学
领域(数学分析)
表现力
数据质量
人工智能
自然语言
质量(理念)
理论计算机科学
数据科学
机器学习
数学分析
哲学
认识论
经济
公制(单位)
数学
运营管理
作者
Alon Halevy,Peter Norvig,Fernando Pereira
出处
期刊:IEEE Intelligent Systems
[Institute of Electrical and Electronics Engineers]
日期:2009-03-01
卷期号:24 (2): 8-12
被引量:1714
摘要
Problems that involve interacting with humans, such as natural language understanding, have not proven to be solvable by concise, neat formulas like F = ma. Instead, the best approach appears to be to embrace the complexity of the domain and address it by harnessing the power of data: if other humans engage in the tasks and generate large amounts of unlabeled, noisy data, new algorithms can be used to build high-quality models from the data.
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