食品安全大数据的融合及分类技术综述

食品是人们赖以生存和发展的基本物质基础,食品安全不仅仅关乎广大消费者的切身利益,甚至关系到国家经济的稳步发展和社会的繁荣昌盛。食品安全大数据具有数据容量大、来源多样、更新速度快、价值密度低却应用价值大的特点,通过将多源的食品安全大数据进行融合及分类并行处理可以帮助人们实现更多的价值。对食品安全大数据融合及分类技术进行了综述。首先,总结了食品安全大数据的来源特征以及数据处理关键技术,阐述了食品安全大数据预处理过程,分析了食品安全大数据融合三种融合层次以及融合关键技术,介绍了食品安全大数据的并行计算模式;然后,归纳了并行分类算法以及几种常见的分类算法,如朴素贝叶斯、决策树、神经网络等;最后,对食品安全大数据做出总结和展望。

Review on Food Safety Big Data Fusion and Classification Technology

Food is the basic material basis for people’s survival and development.Food safety is not only related to the vital interests of consumers,and even related to the steady development of the national economy and social prosperity.Food safety big data has the characteristics of large data capacity,diverse sources,fast update speed,low value density but great application value.The fusion and parallel processing of multi-source food safety big data can help people realize more value.The fusion and classification technology of food safety big data is reviewed.Firstly,we summarize the sources and characteristics of food safety big data and the key technologies of data processing,describe the food safety big data pretreatment process,analyze three fusion levels and key fusion technologies of big data fusion of food safety,and introduce the parallel computing mode of food safety big data.Then,we summarize the parallel classification algorithms and some common classification algorithms,such as naive Bayes,decision tree and neural network.Finally,we summarize and look forward to the big data of food safety.