Knowledge-Based Commercial Real Estate Recommender System

The chapter introduces the theoretical foundations of decision marking for finding commercial real estate based on collaborative filtering, content, knowledge, and hybrid filtering. Special attention is paid to methods using knowledge representation models. The proposed recommender system is based on the production model that determines which recommendations should be applied depending on the given conditions. Based on the query correlating with the user’s interests, preferences, hobbies, past behavior, as well as information about the products and services available in the system, it will be able to determine which recommendations are most suitable for a particular user. In this chapter, practical production rules for finding real estate for a pharmacy, beauty salon and cafe are formulated. The recommender system for the selection of commercial real estate is based on the parsing existing information on popular Russian real estate rental sites, the processing of these data and a knowledge-based model. Also database has been created, as well as web service, the output of which is a Google map with markers of different colors that indicate the degree of recommendation offered to the user.