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首页> 外文期刊>Journal of ambient intelligence and humanized computing >Recommending property with short days-on-market for estate agency
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Recommending property with short days-on-market for estate agency

机译：向房地产中介推荐在市场上待售时间短的房地产

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摘要

Estates with short days-on-market (DOM), referring to the properties whose days on the active market are short, attract realtors to gain commission quickly in transactions. With the rise of the Internet, massive information of on-sale houses can be obtained online. It is a challenge for estate agencies to mine estates with short DOM from such massive information. In this paper, we proposed an estate with short DOM appraisal framework to automatically recommend those estates using transaction data and profile information crawled from websites. Motivated by the estimation process of domain experts, we first seek similar estates with the location, structure and market information of estates. Then, the listing prices of similar estates were used to calculate a price interval. To evaluate the proposed framework, we used two real-world datasets, which consist of 220,000 on-sale estates and 643 estates with manually evaluated values in Chongqing real estate market. The results show that the proposed framework can estimate accurately about 78% estates. Two agencies scored the list of recommendation, in which 88% estates are trustworthy. Compared to the classical hedonic model, our method can successfully deal with problems such as the negative effects of special estates and the lack of labels. Moreover, both the spatial and temporal characteristics of an estate are integrated into our framework. The effect of different parameter settings is also discussed.
机译：短盘交易日（DOM）的房地产是指在活跃市场上交易时间短的房地产，它们吸引房地产经纪人以快速获得交易佣金。随着互联网的兴起，可以在线获取大量的待售房屋信息。对于地产代理来说，从如此大量的信息中挖掘具有短DOM的地产是一个挑战。在本文中，我们提出了一个具有短DOM评估框架的房地产，以使用从网站抓取的交易数据和配置文件信息自动推荐这些房地产。根据领域专家的估计过程，我们首先寻找具有遗产位置，结构和市场信息的相似遗产。然后，使用类似房地产的上市价格来计算价格区间。为了评估所提出的框架，我们使用了两个真实的数据集，包括22万个在售房地产和643个在重庆房地产市场上具有人工评估值的房地产。结果表明，提出的框架可以准确估计约78％的遗产。有两个机构在推荐名单中得分，其中88％的遗产值得信赖。与经典享乐模型相比，我们的方法可以成功处理诸如特殊遗产的负面影响和缺乏标签之类的问题。此外，房地产的时空特征都已整合到我们的框架中。还讨论了不同参数设置的效果。

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