The demand for property valuation has attracted significant attention from sellers, buyers, and customers applying for loans. Reviews of existing approaches have revealed shortcomings in terms of not being able to handle missing value situations, as well as lacking interpretability, which means they cannot be used in real-world applications. To address these challenges, we propose an LLM-Generated EXplainable PRopErty valuation SyStem with neighbor imputation called EXPRESS, which provides the customizable missing value imputation technique, and addresses the opaqueness of prediction by providing the feature-wise explanation generated by LLM. The dynamic nearest neighbor search finds similar properties depending on different application scenarios by property configuration set by users (e.g., house age as criteria for the house in rural areas, and locations for buildings in urban areas). Motivated by the human appraisal procedure, we generate feature-wise explanations to provide users with a more intuitive understanding of the prediction results.

The use of Artificial Intelligence (AI) in the real estate market has been growing in recent years. In this paper, we propose a new method for property valuation that utilizes self-supervised vision transformers, a recent breakthrough in computer vision and deep learning. Our proposed algorithm uses a combination of machine learning, computer vision and hedonic pricing models trained on real estate data to estimate the value of a given property. We collected and pre-processed a data set of real estate properties in the city of Boulder, Colorado and used it to train, validate and test our algorithm. Our data set consisted of qualitative images (including house interiors, exteriors, and street views) as well as quantitative features such as the number of bedrooms, bathrooms, square footage, lot square footage, property age, crime rates, and proximity to amenities. We evaluated the performance of our model using metrics such as Root Mean Squared Error (RMSE). Our findings indicate that these techniques are able to accurately predict the value of properties, with a low RMSE. The proposed algorithm outperforms traditional appraisal methods that do not leverage property images and has the potential to be used in real-world applications.

The idea of AI (Artificial Intelligence) has existed over the last 60 years, often oscillating between periods of high market expectations and stretched dull periods with no concrete developments. However, in current times, AI is no longer just a buzzword and has started making inroads in our daily lives. From search engine recommendations to targeted advertisements, from virtual assistant apps to chatbots, AI is sneaking into our lives. It is going to stay and most probably will make waves in our worlds in the coming times. Naturally, AI has started entering the real estate industry as well.

Dhalia is launching an online valuation tool based on artificial intelligence. The technology works by applying an artificial intelligence model to Dhalia's large database of property values and other local market data. The algorithm scans all data and applies filters to generate an approximate valuation. This valuation is based on various factors including similar properties in the locality and takes into considera tion the size of the property and the number of bedrooms. If the system doesn't find enough data to provide a confident estimate, then clients can request a human valuation which will be provided within 24 hours. This information is then retained within the system and applied to future requests, allowing the AI model to learn from experience.

Real and personal property is a basic delineation in English common law that corresponds roughly to the differences between immovable and movable objects. Interests in land and fixtures, such as permanent buildings, are classified as real property interests. The real estate operations industry consists of companies engaged in developing, renting, leasing, and managing residential and commercial property interests. The industry includes real estate brokerage and agent services, real estate appraisal services, and consulting services. The real estate operations industry excludes real estate investment trusts (REITs).