基于网页浏览内容的心理健康预测模型的研究

Research of Mental Health Prediction Model Based on Web Browsing Content

目前,世界各地的人们都饱受心理健康问题所带来的困扰,这为心理健康问题预防工作带来了新的挑战.如果心理健康状态可以利用网页浏览内容进行预测,就可以为心理健康问题预防工作开辟新的方向.本文探讨了利用用户的网页浏览内容预测其心理健康状态的可行性,并使用支持向量机建立了基于网页浏览内容的心理健康预测模型.为了验证该算法模型的有效性,我们与另外两种算法模型的预测结果进行了对比,结果表明,基于支持向量机的算法模型能够更加有效地预测用户的心理健康状态.

At present, people around the world are suffering from mental health problems, which bring new challenges to the prevention of mental health problems. If mental health can be predicted using web browsing content, it can open up new directions for mental health prevention. In this paper, the feasibility of using the user's web browsing content to predict their mental health is discussed. A support vector machine is used to build a mental health prediction model based on web browsing content. In order to verify the effectiveness of the proposed algorithm, the results of comparison with the other two algorithms were compared. The results show that the algorithm model based on the support vector machine can more effectively predict the user's mental health status.