1 引言 World Wide Web是目前全球最大的信息系统,在WWW上查询Web文档主要依赖于Internet上的索引信息系统,如Yahoo、Infoseek、AltaVista、WebCrawler、Excite、Lycos等等。由于WWW太大又没有良好的结构且Web服务器的自治性,所以Web文...1 引言 World Wide Web是目前全球最大的信息系统,在WWW上查询Web文档主要依赖于Internet上的索引信息系统,如Yahoo、Infoseek、AltaVista、WebCrawler、Excite、Lycos等等。由于WWW太大又没有良好的结构且Web服务器的自治性,所以Web文档的查询难以做到全面而精确。衡量Web文档查询的质量主要有两个方面:①是否能把所有相关的文档资源找出来,不要有所遗漏。展开更多
Influenza is a kind of infectious disease, which spreads quickly and widely. The outbreak of influenza has brought huge losses to society. In this paper, four major categories of flu keywords, “prevention phase”, “...Influenza is a kind of infectious disease, which spreads quickly and widely. The outbreak of influenza has brought huge losses to society. In this paper, four major categories of flu keywords, “prevention phase”, “symptom phase”, “treatment phase”, and “commonly-used phrase” were set. Python web crawler was used to obtain relevant influenza data from the National Influenza Center’s influenza surveillance weekly report and Baidu Index. The establishment of support vector regression (SVR), least absolute shrinkage and selection operator (LASSO), convolutional neural networks (CNN) prediction models through machine learning, took into account the seasonal characteristics of the influenza, also established the time series model (ARMA). The results show that, it is feasible to predict influenza based on web search data. Machine learning shows a certain forecast effect in the prediction of influenza based on web search data. In the future, it will have certain reference value in influenza prediction. The ARMA(3,0) model predicts better results and has greater generalization. Finally, the lack of research in this paper and future research directions are given.展开更多
文摘1 引言 World Wide Web是目前全球最大的信息系统,在WWW上查询Web文档主要依赖于Internet上的索引信息系统,如Yahoo、Infoseek、AltaVista、WebCrawler、Excite、Lycos等等。由于WWW太大又没有良好的结构且Web服务器的自治性,所以Web文档的查询难以做到全面而精确。衡量Web文档查询的质量主要有两个方面:①是否能把所有相关的文档资源找出来,不要有所遗漏。
文摘Influenza is a kind of infectious disease, which spreads quickly and widely. The outbreak of influenza has brought huge losses to society. In this paper, four major categories of flu keywords, “prevention phase”, “symptom phase”, “treatment phase”, and “commonly-used phrase” were set. Python web crawler was used to obtain relevant influenza data from the National Influenza Center’s influenza surveillance weekly report and Baidu Index. The establishment of support vector regression (SVR), least absolute shrinkage and selection operator (LASSO), convolutional neural networks (CNN) prediction models through machine learning, took into account the seasonal characteristics of the influenza, also established the time series model (ARMA). The results show that, it is feasible to predict influenza based on web search data. Machine learning shows a certain forecast effect in the prediction of influenza based on web search data. In the future, it will have certain reference value in influenza prediction. The ARMA(3,0) model predicts better results and has greater generalization. Finally, the lack of research in this paper and future research directions are given.
