The Impact of Community Safety on House Ranking

Abstract

It is well recognized that community safety which affects people's right to live without fear of crime has considerable impacts on housing investments. Housing investors can make more informed decisions if they are fully aware of safety related factors. To this end, we develop a safety-aware house ranking method by incorporating community safety into house assessment. Specifically, we first propose a novel framework to infer community safety level by mining community crime evidences from rich spatio-temporal historical crime data. Then we develop a ranking model which fuses multiply community safety features to rank house value based on the degree of community safety. Finally, we conduct a comprehensive evaluation of the proposed method with real-world crime and house data. The experimental results show that the proposed method substantially outperforms the baseline methods for house ranking.

Meeting Name

16th SIAM International Conference on Data Mining, SDM 2016 (2016: May 5-7, Miami, FL)

Department(s)

Computer Science

Comments

This research was partially supported by Futurewei Technologies, Inc. Also, it was supported in part by Natural Science Foundation of China (71329201).

Keywords and Phrases

Crime; Data mining; Housing; Baseline methods; Community safety; Comprehensive evaluation; Informed decision; Mining communities; Ranking methods; Safety-Related; Spatio temporal; Houses; House ranking; Spatio-temporal

International Standard Book Number (ISBN)

978-1-61197-434-8

International Standard Serial Number (ISSN)

2167-0102 ; 2167-0099

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2016 Society for Industrial and Applied Mathematics (SIAM) Publications, All rights reserved.

Publication Date

01 May 2016

Link to Full Text

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