Математические методы распознавания образов: Тезисы докладов 19-й Всероссийской конференции с международным участием
The rapid growth of geospatial data in the world enables the implementation of
data mining techniques to mine the patterns in geospatial data. In this paper the
authors have applied the algorithms that were previously used for mining slightly
changing patterns in time series to geospatial data of the real estate market. So the
paper discusses mining the patterns that slightly change in space (instead of time).
The paper uses data on the real estate market. The predicted variable (square
meter price) is analyzed respective to the district, distance to the city center, stations
of public transport, highways, shops, sports, entertainment, healthcare, education
centers, offices, parks etc. The proposed approach for mining slightly changing
patterns in geospatial data is highly applicable to any data with geo-tag, e.g. space
image recognition, geo-targeted marketing etc.