Application of a Knowledge Based System in the Real Estate Market

Knowledge plays an increasingly important role in social and economic development, and the construction of a knowledge-based society is the declarative goal of many countries and international organizations. While in the beginning the school system at different levels was responsible for the transfer of knowledge, which took on a sufficiently precise format and was able to fulfill this task, nowadays handling the huge data set is a challenge i.e. the mining of the information and knowledge that can be extracted from it is a challenge. This challenge is tried to be handled with the help of different computer systems. This is especially true in the case of implicit or tacit knowledge, or when mostly qualitative data are available. Using the knowledge based system Doctus, the aim of the present research was to examine how different attributes influence the price of an apartment in the real estate market of Budapest, Hungary and whether consistent conclusion can be expected depending on the change in the structure of the input data. Hypothesis tests were also performed to check the results supplied by the software. Factors such as the property condition, the orientation, the comfort level, and the year of construction were found to be of high importance in determining the price. Surprisingly, the levels of the building, the floor on which the apartment can be found were important as well. Another finding of the present research is that the active presence of the human factor is necessary when using knowledge based systems.