A novel architecture to identify locations for Real Estate Investment

作者：

Highlights：

• The paper discusses the use of data science and network science approaches for solving the location identification problem of real estate investment.

• Both techniques are compared with respect to their time complexities.

• A novel technique that combines the data science and network science is presented and compared with it its time complexities with the previous data science and network science approaches.

• Application of edge differential privacy as a privacy preservation scheme for the real estate network is discussed. In accordance with this a new method called camouflage differential privacy is discussed in detail.

• Application of blockchains as an anonymous transacting platform for real estate location identification is dealt in detail.

摘要

•The paper discusses the use of data science and network science approaches for solving the location identification problem of real estate investment.•Both techniques are compared with respect to their time complexities.•A novel technique that combines the data science and network science is presented and compared with it its time complexities with the previous data science and network science approaches.•Application of edge differential privacy as a privacy preservation scheme for the real estate network is discussed. In accordance with this a new method called camouflage differential privacy is discussed in detail.•Application of blockchains as an anonymous transacting platform for real estate location identification is dealt in detail.

论文关键词：Time complexity,Complex network science,Machine learning,Real estate investment,Data privacy,Blockchains

论文评审过程：Received 18 February 2019, Revised 6 September 2019, Accepted 24 September 2019, Available online 31 October 2019, Version of Record 10 December 2020.

论文官网地址：https://doi.org/10.1016/j.ijinfomgt.2019.09.008