论文标题
基于深度学习的房价预测
House Price Prediction Based On Deep Learning
论文作者
论文摘要
自从远古时代以来，中国人一直在追求的事情非常简单，这无非是“幸福地生活和工作，吃和穿衣服舒适”。今天，改革和开放后40多年，人们基本上已经解决了食物和衣服的问题，紧急问题是住房。如今，由于长期租赁公寓中介平台（例如蛋壳）的风暴，增加了租房者的不安全感以及近年来城市化的不安全感以及主要城市中的人们的争夺，这将使未来的房地产市场竞争更加激烈。为了更好地掌握房地产价格，让消费者合理地购买房屋，并为政府提供制定政策的参考，总结了现有的房屋价格预测的现有方法，并提出了基于混合深度视觉和文本功能的房屋价格预测方法。
Since ancient times, what Chinese people have been pursuing is very simple, which is nothing more than "to live and work happily, to eat and dress comfortable". Today, more than 40 years after the reform and opening, people have basically solved the problem of food and clothing, and the urgent problem is housing. Nowadays, due to the storm of long-term rental apartment intermediary platforms such as eggshell, increasing the sense of insecurity of renters, as well as the urbanization in recent years and the scramble for people in major cities, this will make the future real estate market competition more intense. In order to better grasp the real estate price, let consumers buy a house reasonably, and provide a reference for the government to formulate policies, this paper summarizes the existing methods of house price prediction and proposes a house price prediction method based on mixed depth vision and text features.
