RMIT University
Browse

Visualization-aided personalized exploration of the real estate data

conference contribution
posted on 2024-10-31, 19:30 authored by Mingzhao Li, Zhifeng Bao, Timoleon Sellis, Shi Yan
An efficient analysis of the real estate data is critical for citizens to understand the real estate market and seek appropriate properties to live in or rent. In this paper, after collecting data from different channels and integrating a location-centred comprehensive real estate dataset, we develop HouseSeeker, a visualization-aided analysis system for home-buyers to explore the real estate data, find appropriate properties based on their individual requirements, and compare properties/suburbs from different aspects to discover the strengths and weaknesses of each property/suburb. We demonstrate the effectiveness of our system based on a real-world dataset in Melbourne metropolitan area: it is able to help zero-knowledge users better understand local real estate market and find preferred properties based on their individual requirements. A preliminary implementation of the system is available at http://115.146.89.158/.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1007/978-3-319-46922-5_34
  2. 2.
    ISBN - Is published in 9783319469218 (urn:isbn:9783319469218)

Start page

435

End page

439

Total pages

5

Outlet

Proceedings of the 27th Australasian Database Conference (ADC 2016)

Editors

Muhammad Aamir Cheema, Wenjie Zhang, Lijun Chang

Name of conference

ADC 2016: Databases Theory and Applications

Publisher

Springer

Place published

Swtizerland

Start date

2016-09-28

End date

2016-09-29

Language

English

Copyright

© Springer International Publishing AG 2016

Former Identifier

2006063689

Esploro creation date

2020-06-22

Fedora creation date

2016-10-18

Usage metrics

    Scholarly Works

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC