Abstract
The shift to e-commerce has changed many business areas. Real estate is one of the applications that has been affected by this modern technological wave. Recommender systems are intelligent models that assist users of real estate platforms in finding the best possible properties that fulfill their needs. However, the recommendation task is substantially more challenging in the real estate domain due to the many domain-specific limitations that impair typical recommender systems. For instance, real estate recommender systems usually face the clod-start problem where there are no historical logs for new users or new items, and the recommender system should provide recommendations for these new entities. Therefore, the recommender systems in the real estate market are different and substantially less studied than in other domains. In this article, we aim at providing a comprehensive and systematic literature review on applications of recommender systems in the real estate market. We evaluate a set of research articles (13 journal and 13 conference papers) which represent the majority of research and commercial solutions proposed in the field of real estate recommender systems. These papers have been reviewed and categorized based on their methodological approaches, the main challenges that they addressed, and their evaluation procedures. Based on these categorizations, we outlined some possible directions for future research.
Highlights
In the age of digitalization, people use online platforms to find their desired items.These platforms usually have a huge catalog of items, which makes it difficult for their users to find only a short list of desired items out of many other irrelevant items
We do acknowledge the importance of all the aforementioned applications, in this paper, we focus on the real estate market as we deem that this field has not been adequately explored, and its particular recommendation challenges have not been well studied in the past years
We reviewed the type of datasets that were used, their evaluation strategies, the corresponding performance measures, and the baselines that were employed in the benchmarking
Summary
In the age of digitalization, people use online platforms to find their desired items. We identify the specific challenges that real estate RSs face, such as the cold-start problem, the integration of rich item features, the handling of the complex buying behavior, conflicting criteria, and existing data sparsity.
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