The research development of hedonic price model-based real estate appraisal in the era of big data
In the era of big data, advances in relevant technologies are profoundly impacting the field of
real estate appraisal. Many scholars regard the integration of big data technology as an …
real estate appraisal. Many scholars regard the integration of big data technology as an …
Understanding house price appreciation using multi-source big geo-data and machine learning
Understanding house price appreciation benefits place-based decision makings and real
estate market analyses. Although large amounts of interests have been paid in the house …
estate market analyses. Although large amounts of interests have been paid in the house …
Housing price prediction incorporating spatio-temporal dependency into machine learning algorithms
Conventional housing price prediction methods rarely consider the spatiotemporal non-
stationary problem in a large data volumes. In this study, four machine learning (ML) models …
stationary problem in a large data volumes. In this study, four machine learning (ML) models …
A modelling approach with geographically weighted regression methods for determining geographic variation and influencing factors in housing price: A case in …
S Sisman, AC Aydinoglu - Land use policy, 2022 - Elsevier
Determining real estate market dynamics has become an important issue in the city
economy for achieving sustainable urban land management and investment planning. This …
economy for achieving sustainable urban land management and investment planning. This …
Learning urban region representations with POIs and hierarchical graph infomax
We present the hierarchical graph infomax (HGI) approach for learning urban region
representations (vector embeddings) with points-of-interest (POIs) in a fully unsupervised …
representations (vector embeddings) with points-of-interest (POIs) in a fully unsupervised …
Human settlement value assessment from a place perspective: Considering human dynamics and perceptions in house price modeling
A better formalization of place-where people live, perceive, and interact with others-is crucial
for understanding socioeconomic environment and human settlement. The widely used …
for understanding socioeconomic environment and human settlement. The widely used …
Incorporating neighborhoods with explainable artificial intelligence for modeling fine-scale housing prices
The hedonic price model (HPM) has been widely used to investigate the association
between neighborhoods and housing prices. Empirical studies of HPM assume that mixed …
between neighborhoods and housing prices. Empirical studies of HPM assume that mixed …
Just smart or just and smart cities? Assessing the literature on housing and information and communication technology
S Shamsuddin, S Srinivasan - Housing Policy Debate, 2021 - Taylor & Francis
Housing issues, including affordability, instability, and the search for available units, present
ongoing challenges for urban inhabitants. Supporters claim information and communication …
ongoing challenges for urban inhabitants. Supporters claim information and communication …
Housing price variations using spatio-temporal data mining techniques
The issue of property evaluation and appraisal has been of high interest for private and
public agents involved in the housing industry for the purposes of trade, insurance and tax …
public agents involved in the housing industry for the purposes of trade, insurance and tax …
Geographically and temporally neural network weighted regression for modeling spatiotemporal non-stationary relationships
Geographically weighted regression (GWR) and geographically and temporally weighted
regression (GTWR) are classic methods for estimating non-stationary relationships …
regression (GTWR) are classic methods for estimating non-stationary relationships …