中文摘要：

大数据蕴含巨大的社会、经济、科学价值，已成为学术界与企业界关注的重点。其关键技术可划分为三大层次：数据平台、分析平台和展示平台，其中分析平台是大数据转化为价值的桥梁。一般来说，大数据拥有体量浩大（volume）、多源异构（variety）、生成快速（velocity）、价值稀疏（value）的“4V”特性，扩大了大数据的价值空间，同时也为大数据的分析技术带来巨大挑战。其中三大挑战比较显著，即多源异构大数据、大量非结构化数据存储、大数据价值稀疏且变化快。其三大核心科学问题为大数据的表达、存储和预测问题。由于传统的数据分析方法难以胜任，发展新的大数据分析方法势在必然。人脑是天然的大数据处理引擎。神经网络是一种模拟人脑大数据分析机制的计算方法，是目前大数据分析中最成功的方法。神经网络的研究主要包括：模拟大脑神经网络结构，构建神经网络结构模型；模拟大脑神经网络的记忆机制，发展学习算法。神经网络的研究历史历经波折。近年来，随着当代计算机计算能力的不断提升，基于神经网络的大数据分析方法取得了巨大成功，尤其是在各应用领域，如语音大数据分析、图像大数据分析、医学大数据分析等，引领了人工智能的发展。AlphaGo在人机围棋大战中获胜，引起了广泛关注。“大数据＋神经网络”已成为驱动创新、推动社会发展和改变人类生产生活方式的一种重要力量。以大数据和神经网络为线索，回顾大数据的基本概念与关键技术，梳理神经网络研究的基本框架，可以发现它们之间默契切合、互相促进的关系。一方面，神经网络具有强大的特征提取与抽象能力，能够整合多源信息，处理异构数据，捕捉变化动态，是大数据实现价值转化的桥梁。另一方面，体量浩大的大数据为神

英文摘要：

Big data contains the high social, economic, and scientific value. It has been being spotlighted all around the academia and industry. The key technology can be divide into three levels ： the data platform, the analysis platform, and the presentation platform. Among these, analysis platform is the bridge that transforms big data into real value. Generally, there are four specific attributes of big data, known as the volume, variety, velocity, and value. They extend the value space of big data. Meanwhile, they become great challenges of big data analysis. There are three major issues：Multi-sourced and heterogeneous big data, storage of tremendous unstructured data, and sparse value in fast changing big data. The three central scientific problems in big data analysis are representation, storage, and prediction of big data. Traditional methods cannot handle big data well. New methods for big data are imperative. Human brains are naturally excellent big data processor. Neural networks are computational replications of big data analysis principles in human brains. Neural networks are the most successful methods for big data analysis. Simulating neural structure in the brain to build neural network structure models and simulating memory mechanism in the brain to develop learning algorithms are two basic methodology in neural networks research. The history of neural networks research has ups and downs. Today, with the support from developing computational power, big data analysis using neural networks has achieved great success, especially in big data applications, for example, audio big data analysis, visual big data analysis, medical big data analysis. Neural networks are leading the artificial-intelligence researches. AlphaGo beating human champion in Go game attracted even more public interest. ＂Big data ＋ Neural Networks＂ is becoming one of the driving forces of innovation, social promotion, and living development. It can be clearly demonstrated how perfectly matched and mutually reinforcing are big data