Reasonable Price Recommendation on Airbnb Using Multi-Scale Clustering

被引：0

作者：

Li, Yang ^{[1
]}

Pan, Quan ^{[1
]}

Yang, Tao ^{[1
,2
]}

Guo, Lantian ^{[1
]}

机构：

[1] Chinese Acad Sci, Northwestern Polytech Univ, Sch Automat, Xin 710072, Shanxi, Peoples R China

[2] Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xin 710049, Shanxi, Peoples R China

来源：

PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016 | 2016年

关键词：

Multi-Scale Affinity Propagation(MSAP); cluster; Linear Regression model with Normal Noise(LRNN); price prediction;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Reasonable house price prediction is a meaningful task, and the house clustering is an important process in the prediction. In this paper, we propose the method of Multi-Scale Affinity Propagation(MSAP) aggregating the house appropriately by the landmark and the facility. Then in each cluster, using Linear Regression model with Normal Noise(LRNN) predicts the reasonable price, which is verified by the increasing number of the renting reviews. Experiments show that the precision of the reasonable price prediction improved greatly via the method of MSAP.

引用

下载

页码：7038 / 7041

页数：4

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