中国饮食相关心血管代谢疾病的数据挖掘方法

Angela Chang, Jieyi Hu, Yichao Liu, M. Liu
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引用次数: 3

摘要

数据挖掘是在数据集中发现有价值的和新颖的结构。考虑到与饮食有关的心脏代谢增加的人数,这使媒体在食品和健康宣传方面的努力受到质疑。本研究的主要目标之一是关注新兴的数据挖掘方法,以了解新闻媒体讨论食物、饮食和相关心脏代谢疾病的结构和方式。总共有6625个项目涉及食品、香料、调味品以及心脏代谢疾病。数据挖掘算法涉及预测健康结果和提供政策信息的食品。食品数据语料库最典型的用法是从文本自动转换到更大的文化力量上的健康问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Mining Approach to Chinese Food Analysis for Diet-Related Cardiometabolic Diseases
Data mining is the discovery of valuable and novel structures in datasets. Considering the number of people suffering from diet-related cardiometabolic increase, it brings into question the media's efforts in food and health communication. One of the main objectives in this study focuses on the emerging data mining methodology to understand the structure of what and how the news media discuss food, diet, and the related cardiometabolic diseases. A total of 6,625 items of coverage on food, flavor, and condiments along with cardiometabolic diseases is identified. Data mining algorithms concern food for predicting health outcomes and providing policy information. The most typical usage of a food data corpus is automatic conversion from text to health afflictions on larger cultural forces.
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