论文标题
公寓平面图的主观功能和舒适性预测及其在直观搜索中的应用
Subjective Functionality and Comfort Prediction for Apartment Floor Plans and Its Application to Intuitive Searches
论文作者
论文摘要
这项研究介绍了使用功能和舒适性作为查询项目的公寓搜索中的新用户体验。这项研究有三个技术贡献。首先，我们使用九个问题陈述介绍了有关舒适，开放性，隐私等水平的住宅平面图的感知功能和舒适得分的新数据集。其次，我们提出了一种算法来预测平面图图像中的分数。最后，我们实施了一个新的公寓搜索系统，并使用众包进行了大规模的可用性研究。实验结果表明，我们的公寓搜索系统可以提供更好的用户体验。据我们所知，这项研究是第一项提出一种高度准确的预测模型，以使用机器学习来实现主观功能和舒适性。
This study presents a new user experience in apartment searches using functionality and comfort as query items. This study has three technical contributions. First, we present a new dataset on the perceived functionality and comfort scores of residential floor plans using nine question statements about the level of comfort, openness, privacy, etc. Second, we propose an algorithm to predict the scores from the floor plan images. Lastly, we implement a new apartment search system and conduct a large-scale usability study using crowdsourcing. The experimental results show that our apartment search system can provide a better user experience. To the best of our knowledge, this study is the first work to propose a highly accurate prediction model for the subjective functionality and comfort of apartments using machine learning.
