Senin, 11 Februari 2008

Analyzing the Real Estate Market - Part 2

In the previous part i listed the first steps required that can turn unstructured information of flat adverts for rent to a suitable form for further analysis of the Greek Real Estate Market.

Once the Information Extraction step is finished, the characteristics of each flat advert (price, square meters, type of heating, years old etc) are inserted into a database. Once flat adverts data are inserted, we are able to extract key information about price trends for specific areas of Athens such as Nea Smyrni. The following screen capture shows a portion of the records that exist in the database, after the information extraction phase :



With the advert data in place we are ready to deploy data mining algorithms that can reveal to us potentially useful patterns. For example, a classification analysis aimed in finding which characteristics are important to obtain a high renting price produces the following decision tree :




The decision tree depicted above essentially gives us the following information :

  • The most important characteristic for obtaining a high renting value (in terms of Euros per square meter) is the provision of a parking space with the flat.
  • If a flat provides a parking space, has a storage area and has up to two bed rooms then the flat obtains the highest renting rate, (ie 7.54 Euros per square meter)
  • If a flat does not provide a parking space but has at least one bedroom and is located at the fourth floor (or higher) then the flat obtains the highest renting rate per square meter.









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